Overview

Dataset statistics

Number of variables54
Number of observations171
Missing cells2483
Missing cells (%)26.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory72.3 KiB
Average record size in memory432.7 B

Variable types

Numeric14
Text19
Categorical18
Unsupported2
DateTime1

Alerts

airdate has constant value ""Constant
id is highly overall correlated with _embedded.show.weight and 3 other fieldsHigh correlation
season is highly overall correlated with _embedded.show.id and 4 other fieldsHigh correlation
number is highly overall correlated with type and 8 other fieldsHigh correlation
runtime is highly overall correlated with _embedded.show.runtime and 10 other fieldsHigh correlation
rating.average is highly overall correlated with _embedded.show.rating.average and 13 other fieldsHigh correlation
_embedded.show.id is highly overall correlated with season and 7 other fieldsHigh correlation
_embedded.show.runtime is highly overall correlated with runtime and 11 other fieldsHigh correlation
_embedded.show.averageRuntime is highly overall correlated with runtime and 12 other fieldsHigh correlation
_embedded.show.rating.average is highly overall correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.weight is highly overall correlated with id and 7 other fieldsHigh correlation
_embedded.show.webChannel.id is highly overall correlated with _embedded.show.webChannel.country.name and 8 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly overall correlated with season and 10 other fieldsHigh correlation
_embedded.show.updated is highly overall correlated with _embedded.show.webChannel.officialSite and 5 other fieldsHigh correlation
_embedded.show.network.id is highly overall correlated with id and 16 other fieldsHigh correlation
type is highly overall correlated with number and 8 other fieldsHigh correlation
airtime is highly overall correlated with number and 11 other fieldsHigh correlation
airstamp is highly overall correlated with number and 15 other fieldsHigh correlation
_embedded.show.type is highly overall correlated with rating.average and 7 other fieldsHigh correlation
_embedded.show.language is highly overall correlated with rating.average and 12 other fieldsHigh correlation
_embedded.show.status is highly overall correlated with _embedded.show.network.id and 7 other fieldsHigh correlation
_embedded.show.ended is highly overall correlated with season and 22 other fieldsHigh correlation
_embedded.show.schedule.time is highly overall correlated with rating.average and 10 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly overall correlated with runtime and 16 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly overall correlated with runtime and 16 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly overall correlated with runtime and 16 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly overall correlated with runtime and 24 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly overall correlated with id and 16 other fieldsHigh correlation
_embedded.show.network.country.name is highly overall correlated with number and 23 other fieldsHigh correlation
_embedded.show.network.country.code is highly overall correlated with number and 23 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly overall correlated with number and 23 other fieldsHigh correlation
_embedded.show.network.officialSite is highly overall correlated with id and 28 other fieldsHigh correlation
type is highly imbalanced (93.5%)Imbalance
airtime is highly imbalanced (61.6%)Imbalance
_embedded.show.schedule.time is highly imbalanced (64.1%)Imbalance
number has 2 (1.2%) missing valuesMissing
runtime has 11 (6.4%) missing valuesMissing
summary has 92 (53.8%) missing valuesMissing
rating.average has 139 (81.3%) missing valuesMissing
_embedded.show.language has 6 (3.5%) missing valuesMissing
_embedded.show.runtime has 109 (63.7%) missing valuesMissing
_embedded.show.averageRuntime has 12 (7.0%) missing valuesMissing
_embedded.show.ended has 106 (62.0%) missing valuesMissing
_embedded.show.officialSite has 17 (9.9%) missing valuesMissing
_embedded.show.rating.average has 128 (74.9%) missing valuesMissing
_embedded.show.webChannel.id has 4 (2.3%) missing valuesMissing
_embedded.show.webChannel.name has 4 (2.3%) missing valuesMissing
_embedded.show.webChannel.country.name has 67 (39.2%) missing valuesMissing
_embedded.show.webChannel.country.code has 67 (39.2%) missing valuesMissing
_embedded.show.webChannel.country.timezone has 67 (39.2%) missing valuesMissing
_embedded.show.webChannel.officialSite has 39 (22.8%) missing valuesMissing
_embedded.show.externals.tvrage has 169 (98.8%) missing valuesMissing
_embedded.show.externals.thetvdb has 53 (31.0%) missing valuesMissing
_embedded.show.externals.imdb has 88 (51.5%) missing valuesMissing
_embedded.show.image.medium has 8 (4.7%) missing valuesMissing
_embedded.show.image.original has 8 (4.7%) missing valuesMissing
_embedded.show.summary has 37 (21.6%) missing valuesMissing
image.medium has 91 (53.2%) missing valuesMissing
image.original has 91 (53.2%) missing valuesMissing
_embedded.show.network.id has 149 (87.1%) missing valuesMissing
_embedded.show.network.name has 149 (87.1%) missing valuesMissing
_embedded.show.network.country.name has 149 (87.1%) missing valuesMissing
_embedded.show.network.country.code has 149 (87.1%) missing valuesMissing
_embedded.show.network.country.timezone has 149 (87.1%) missing valuesMissing
_embedded.show.network.officialSite has 159 (93.0%) missing valuesMissing
_embedded.show._links.nextepisode.href has 164 (95.9%) missing valuesMissing
_embedded.show.externals.tvrage is uniformly distributedUniform
id has unique valuesUnique
url has unique valuesUnique
_links.self.href has unique valuesUnique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysisUnsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-08-13 20:44:50.231446
Analysis finished2023-08-13 20:45:03.780173
Duration13.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2444653.7
Minimum2323161
Maximum2603381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:03.836731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2323161
5-th percentile2400189
Q12427729
median2438318
Q32452719.5
95-th percentile2517978.5
Maximum2603381
Range280220
Interquartile range (IQR)24990.5

Descriptive statistics

Standard deviation38178.061
Coefficient of variation (CV)0.01561696
Kurtosis4.8623154
Mean2444653.7
Median Absolute Deviation (MAD)14399
Skewness1.3728024
Sum4.1803579 × 108
Variance1.4575643 × 109
MonotonicityNot monotonic
2023-08-13T15:45:03.919553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2450906 1
 
0.6%
2442731 1
 
0.6%
2454076 1
 
0.6%
2454077 1
 
0.6%
2442332 1
 
0.6%
2440940 1
 
0.6%
2442203 1
 
0.6%
2441097 1
 
0.6%
2489442 1
 
0.6%
2438066 1
 
0.6%
Other values (161) 161
94.2%
ValueCountFrequency (%)
2323161 1
0.6%
2327473 1
0.6%
2372672 1
0.6%
2372683 1
0.6%
2393535 1
0.6%
2395103 1
0.6%
2397824 1
0.6%
2399082 1
0.6%
2399220 1
0.6%
2401158 1
0.6%
ValueCountFrequency (%)
2603381 1
0.6%
2577817 1
0.6%
2573107 1
0.6%
2572524 1
0.6%
2568631 1
0.6%
2568630 1
0.6%
2550682 1
0.6%
2519147 1
0.6%
2517979 1
0.6%
2517978 1
0.6%

url
Text

UNIQUE 

Distinct171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:04.234246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length146
Median length103
Mean length79.081871
Min length59

Characters and Unicode

Total characters13523
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2450906/hocu-vse-znat-2x87-seria-87
2nd rowhttps://www.tvmaze.com/episodes/2450907/hocu-vse-znat-2x88-seria-88
3rd rowhttps://www.tvmaze.com/episodes/2438114/restoran-po-ponatiam-2x05-seria-15
4th rowhttps://www.tvmaze.com/episodes/2438115/restoran-po-ponatiam-2x06-seria-16
5th rowhttps://www.tvmaze.com/episodes/2413779/alisa-ne-mozet-zdat-1x08-8-seria
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2450906/hocu-vse-znat-2x87-seria-87 1
 
0.6%
https://www.tvmaze.com/episodes/2433630/zamerzsie-1x05-seria-5 1
 
0.6%
https://www.tvmaze.com/episodes/2476693/neizvestnoe-budusee-1x01-seria-1 1
 
0.6%
https://www.tvmaze.com/episodes/2438114/restoran-po-ponatiam-2x05-seria-15 1
 
0.6%
https://www.tvmaze.com/episodes/2438115/restoran-po-ponatiam-2x06-seria-16 1
 
0.6%
https://www.tvmaze.com/episodes/2413779/alisa-ne-mozet-zdat-1x08-8-seria 1
 
0.6%
https://www.tvmaze.com/episodes/2323161/zamerzsie-1x01-seria-1 1
 
0.6%
https://www.tvmaze.com/episodes/2433627/zamerzsie-1x02-seria-2 1
 
0.6%
https://www.tvmaze.com/episodes/2433628/zamerzsie-1x03-seria-3 1
 
0.6%
https://www.tvmaze.com/episodes/2433629/zamerzsie-1x04-seria-4 1
 
0.6%
Other values (161) 161
94.2%
2023-08-13T15:45:04.644337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1131
 
8.4%
- 1016
 
7.5%
s 872
 
6.4%
/ 855
 
6.3%
t 801
 
5.9%
o 720
 
5.3%
a 594
 
4.4%
w 579
 
4.3%
i 540
 
4.0%
p 499
 
3.7%
Other values (30) 5916
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9253
68.4%
Decimal Number 1886
 
13.9%
Other Punctuation 1368
 
10.1%
Dash Punctuation 1016
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1131
12.2%
s 872
 
9.4%
t 801
 
8.7%
o 720
 
7.8%
a 594
 
6.4%
w 579
 
6.3%
i 540
 
5.8%
p 499
 
5.4%
m 452
 
4.9%
d 362
 
3.9%
Other values (16) 2703
29.2%
Decimal Number
ValueCountFrequency (%)
2 361
19.1%
1 323
17.1%
4 266
14.1%
0 238
12.6%
3 201
10.7%
5 117
 
6.2%
8 105
 
5.6%
6 103
 
5.5%
7 87
 
4.6%
9 85
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/ 855
62.5%
. 342
 
25.0%
: 171
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1016
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9253
68.4%
Common 4270
31.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1131
12.2%
s 872
 
9.4%
t 801
 
8.7%
o 720
 
7.8%
a 594
 
6.4%
w 579
 
6.3%
i 540
 
5.8%
p 499
 
5.4%
m 452
 
4.9%
d 362
 
3.9%
Other values (16) 2703
29.2%
Common
ValueCountFrequency (%)
- 1016
23.8%
/ 855
20.0%
2 361
 
8.5%
. 342
 
8.0%
1 323
 
7.6%
4 266
 
6.2%
0 238
 
5.6%
3 201
 
4.7%
: 171
 
4.0%
5 117
 
2.7%
Other values (4) 380
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1131
 
8.4%
- 1016
 
7.5%
s 872
 
6.4%
/ 855
 
6.3%
t 801
 
5.9%
o 720
 
5.3%
a 594
 
4.4%
w 579
 
4.3%
i 540
 
4.0%
p 499
 
3.7%
Other values (30) 5916
43.7%

name
Text

Distinct149
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:04.882382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length52
Mean length15.871345
Min length3

Characters and Unicode

Total characters2714
Distinct characters144
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)79.5%

Sample

1st rowСерия 87
2nd rowСерия 88
3rd rowСерия 15
4th rowСерия 16
5th row8 серия
ValueCountFrequency (%)
episode 31
 
6.0%
серия 26
 
5.0%
the 15
 
2.9%
1 12
 
2.3%
2 9
 
1.7%
a 8
 
1.5%
6 7
 
1.3%
odcinek 6
 
1.2%
3 6
 
1.2%
and 5
 
1.0%
Other values (339) 395
76.0%
2023-08-13T15:45:05.205807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
349
 
12.9%
e 214
 
7.9%
o 157
 
5.8%
i 120
 
4.4%
s 119
 
4.4%
a 109
 
4.0%
n 98
 
3.6%
t 90
 
3.3%
d 86
 
3.2%
r 73
 
2.7%
Other values (134) 1299
47.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1752
64.6%
Uppercase Letter 414
 
15.3%
Space Separator 349
 
12.9%
Decimal Number 122
 
4.5%
Other Punctuation 38
 
1.4%
Other Letter 30
 
1.1%
Dash Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other values (4) 4
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 214
 
12.2%
o 157
 
9.0%
i 120
 
6.8%
s 119
 
6.8%
a 109
 
6.2%
n 98
 
5.6%
t 90
 
5.1%
d 86
 
4.9%
r 73
 
4.2%
p 63
 
3.6%
Other values (51) 623
35.6%
Uppercase Letter
ValueCountFrequency (%)
E 55
 
13.3%
T 38
 
9.2%
С 30
 
7.2%
S 23
 
5.6%
A 21
 
5.1%
D 20
 
4.8%
P 18
 
4.3%
B 18
 
4.3%
O 18
 
4.3%
W 15
 
3.6%
Other values (34) 158
38.2%
Other Letter
ValueCountFrequency (%)
ا 7
23.3%
ل 7
23.3%
ة 3
10.0%
ح 2
 
6.7%
ق 2
 
6.7%
ي 2
 
6.7%
م 2
 
6.7%
ن 2
 
6.7%
ك 1
 
3.3%
ت 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 31
25.4%
3 19
15.6%
2 18
14.8%
8 12
 
9.8%
4 11
 
9.0%
6 10
 
8.2%
5 9
 
7.4%
0 7
 
5.7%
7 3
 
2.5%
9 2
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 7
18.4%
' 7
18.4%
? 6
15.8%
, 5
13.2%
" 4
10.5%
: 4
10.5%
! 3
7.9%
¿ 1
 
2.6%
1
 
2.6%
Space Separator
ValueCountFrequency (%)
349
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 1
100.0%
Final Punctuation
ValueCountFrequency (%)
» 1
100.0%
Currency Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1842
67.9%
Common 518
 
19.1%
Cyrillic 324
 
11.9%
Arabic 30
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 214
 
11.6%
o 157
 
8.5%
i 120
 
6.5%
s 119
 
6.5%
a 109
 
5.9%
n 98
 
5.3%
t 90
 
4.9%
d 86
 
4.7%
r 73
 
4.0%
p 63
 
3.4%
Other values (51) 713
38.7%
Cyrillic
ValueCountFrequency (%)
и 44
13.6%
е 37
11.4%
р 34
 
10.5%
С 30
 
9.3%
я 27
 
8.3%
о 16
 
4.9%
а 16
 
4.9%
с 13
 
4.0%
т 10
 
3.1%
д 9
 
2.8%
Other values (34) 88
27.2%
Common
ValueCountFrequency (%)
349
67.4%
1 31
 
6.0%
3 19
 
3.7%
2 18
 
3.5%
8 12
 
2.3%
4 11
 
2.1%
6 10
 
1.9%
5 9
 
1.7%
. 7
 
1.4%
' 7
 
1.4%
Other values (18) 45
 
8.7%
Arabic
ValueCountFrequency (%)
ا 7
23.3%
ل 7
23.3%
ة 3
10.0%
ح 2
 
6.7%
ق 2
 
6.7%
ي 2
 
6.7%
م 2
 
6.7%
ن 2
 
6.7%
ك 1
 
3.3%
ت 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2341
86.3%
Cyrillic 324
 
11.9%
Arabic 30
 
1.1%
None 16
 
0.6%
Letterlike Symbols 1
 
< 0.1%
Punctuation 1
 
< 0.1%
Currency Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
349
 
14.9%
e 214
 
9.1%
o 157
 
6.7%
i 120
 
5.1%
s 119
 
5.1%
a 109
 
4.7%
n 98
 
4.2%
t 90
 
3.8%
d 86
 
3.7%
r 73
 
3.1%
Other values (64) 926
39.6%
Cyrillic
ValueCountFrequency (%)
и 44
13.6%
е 37
11.4%
р 34
 
10.5%
С 30
 
9.3%
я 27
 
8.3%
о 16
 
4.9%
а 16
 
4.9%
с 13
 
4.0%
т 10
 
3.1%
д 9
 
2.8%
Other values (34) 88
27.2%
Arabic
ValueCountFrequency (%)
ا 7
23.3%
ل 7
23.3%
ة 3
10.0%
ح 2
 
6.7%
ق 2
 
6.7%
ي 2
 
6.7%
م 2
 
6.7%
ن 2
 
6.7%
ك 1
 
3.3%
ت 1
 
3.3%
None
ValueCountFrequency (%)
ä 3
18.8%
ö 2
12.5%
á 2
12.5%
ñ 1
 
6.2%
í 1
 
6.2%
¿ 1
 
6.2%
ó 1
 
6.2%
ã 1
 
6.2%
ú 1
 
6.2%
Ä 1
 
6.2%
Other values (2) 2
12.5%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.017544
Minimum1
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:05.296660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile20.5
Maximum2022
Range2021
Interquartile range (IQR)2

Descriptive statistics

Standard deviation341.19662
Coefficient of variation (CV)5.5016146
Kurtosis30.124444
Mean62.017544
Median Absolute Deviation (MAD)0
Skewness5.6359974
Sum10605
Variance116415.13
MonotonicityNot monotonic
2023-08-13T15:45:05.365037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 111
64.9%
2 16
 
9.4%
3 11
 
6.4%
2022 5
 
2.9%
4 5
 
2.9%
5 4
 
2.3%
13 2
 
1.2%
6 2
 
1.2%
11 2
 
1.2%
9 2
 
1.2%
Other values (11) 11
 
6.4%
ValueCountFrequency (%)
1 111
64.9%
2 16
 
9.4%
3 11
 
6.4%
4 5
 
2.9%
5 4
 
2.3%
6 2
 
1.2%
7 1
 
0.6%
8 1
 
0.6%
9 2
 
1.2%
10 1
 
0.6%
ValueCountFrequency (%)
2022 5
2.9%
39 1
 
0.6%
28 1
 
0.6%
23 1
 
0.6%
22 1
 
0.6%
19 1
 
0.6%
17 1
 
0.6%
16 1
 
0.6%
13 2
 
1.2%
12 1
 
0.6%

number
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)26.6%
Missing2
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean18.940828
Minimum1
Maximum265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:05.440206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q312
95-th percentile88.6
Maximum265
Range264
Interquartile range (IQR)9

Descriptive statistics

Standard deviation39.999361
Coefficient of variation (CV)2.1118063
Kurtosis19.074082
Mean18.940828
Median Absolute Deviation (MAD)4
Skewness4.1083447
Sum3201
Variance1599.9489
MonotonicityNot monotonic
2023-08-13T15:45:05.516643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 22
12.9%
6 16
 
9.4%
2 16
 
9.4%
3 16
 
9.4%
4 14
 
8.2%
5 12
 
7.0%
8 10
 
5.8%
11 6
 
3.5%
7 5
 
2.9%
12 5
 
2.9%
Other values (35) 47
27.5%
ValueCountFrequency (%)
1 22
12.9%
2 16
9.4%
3 16
9.4%
4 14
8.2%
5 12
7.0%
6 16
9.4%
7 5
 
2.9%
8 10
5.8%
9 1
 
0.6%
10 4
 
2.3%
ValueCountFrequency (%)
265 1
0.6%
240 1
0.6%
238 1
0.6%
152 1
0.6%
138 1
0.6%
116 1
0.6%
115 1
0.6%
96 1
0.6%
89 1
0.6%
88 1
0.6%

type
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
regular
169 
significant_special
 
1
insignificant_special
 
1

Length

Max length21
Median length7
Mean length7.1520468
Min length7

Characters and Unicode

Total characters1223
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 169
98.8%
significant_special 1
 
0.6%
insignificant_special 1
 
0.6%

Length

2023-08-13T15:45:05.589369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:05.654986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 169
98.8%
significant_special 1
 
0.6%
insignificant_special 1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
r 338
27.6%
a 173
14.1%
e 171
14.0%
g 171
14.0%
l 171
14.0%
u 169
13.8%
i 9
 
0.7%
n 5
 
0.4%
s 4
 
0.3%
c 4
 
0.3%
Other values (4) 8
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1221
99.8%
Connector Punctuation 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 338
27.7%
a 173
14.2%
e 171
14.0%
g 171
14.0%
l 171
14.0%
u 169
13.8%
i 9
 
0.7%
n 5
 
0.4%
s 4
 
0.3%
c 4
 
0.3%
Other values (3) 6
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1221
99.8%
Common 2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 338
27.7%
a 173
14.2%
e 171
14.0%
g 171
14.0%
l 171
14.0%
u 169
13.8%
i 9
 
0.7%
n 5
 
0.4%
s 4
 
0.3%
c 4
 
0.3%
Other values (3) 6
 
0.5%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1223
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 338
27.6%
a 173
14.1%
e 171
14.0%
g 171
14.0%
l 171
14.0%
u 169
13.8%
i 9
 
0.7%
n 5
 
0.4%
s 4
 
0.3%
c 4
 
0.3%
Other values (4) 8
 
0.7%

airdate
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2022-12-01
171 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1710
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-01
2nd row2022-12-01
3rd row2022-12-01
4th row2022-12-01
5th row2022-12-01

Common Values

ValueCountFrequency (%)
2022-12-01 171
100.0%

Length

2023-08-13T15:45:05.717644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:05.772459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 171
100.0%

Most occurring characters

ValueCountFrequency (%)
2 684
40.0%
0 342
20.0%
- 342
20.0%
1 342
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1368
80.0%
Dash Punctuation 342
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 684
50.0%
0 342
25.0%
1 342
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1710
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 684
40.0%
0 342
20.0%
- 342
20.0%
1 342
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 684
40.0%
0 342
20.0%
- 342
20.0%
1 342
20.0%

airtime
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
131 
06:00
 
11
12:00
 
5
22:00
 
3
10:00
 
3
Other values (14)
18 

Length

Max length5
Median length0
Mean length1.1695906
Min length0

Characters and Unicode

Total characters200
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)6.4%

Sample

1st row
2nd row
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
131
76.6%
06:00 11
 
6.4%
12:00 5
 
2.9%
22:00 3
 
1.8%
10:00 3
 
1.8%
00:00 3
 
1.8%
17:35 2
 
1.2%
19:00 2
 
1.2%
20:30 1
 
0.6%
11:00 1
 
0.6%
Other values (9) 9
 
5.3%

Length

2023-08-13T15:45:05.829886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:00 11
27.5%
12:00 5
12.5%
22:00 3
 
7.5%
10:00 3
 
7.5%
00:00 3
 
7.5%
17:35 2
 
5.0%
19:00 2
 
5.0%
21:00 1
 
2.5%
19:30 1
 
2.5%
19:25 1
 
2.5%
Other values (8) 8
20.0%

Most occurring characters

ValueCountFrequency (%)
0 89
44.5%
: 40
20.0%
1 21
 
10.5%
2 16
 
8.0%
6 11
 
5.5%
5 7
 
3.5%
9 6
 
3.0%
3 5
 
2.5%
7 4
 
2.0%
8 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
80.0%
Other Punctuation 40
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
55.6%
1 21
 
13.1%
2 16
 
10.0%
6 11
 
6.9%
5 7
 
4.4%
9 6
 
3.8%
3 5
 
3.1%
7 4
 
2.5%
8 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
: 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
44.5%
: 40
20.0%
1 21
 
10.5%
2 16
 
8.0%
6 11
 
5.5%
5 7
 
3.5%
9 6
 
3.0%
3 5
 
2.5%
7 4
 
2.0%
8 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
44.5%
: 40
20.0%
1 21
 
10.5%
2 16
 
8.0%
6 11
 
5.5%
5 7
 
3.5%
9 6
 
3.0%
3 5
 
2.5%
7 4
 
2.0%
8 1
 
0.5%

airstamp
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2022-12-01T12:00:00+00:00
69 
2022-12-01T00:00:00+00:00
24 
2022-12-01T17:00:00+00:00
14 
2022-12-01T06:00:00+00:00
2022-12-01T01:00:00+00:00
Other values (21)
47 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters4275
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)7.6%

Sample

1st row2022-12-01T00:00:00+00:00
2nd row2022-12-01T00:00:00+00:00
3rd row2022-12-01T00:00:00+00:00
4th row2022-12-01T00:00:00+00:00
5th row2022-12-01T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2022-12-01T12:00:00+00:00 69
40.4%
2022-12-01T00:00:00+00:00 24
 
14.0%
2022-12-01T17:00:00+00:00 14
 
8.2%
2022-12-01T06:00:00+00:00 9
 
5.3%
2022-12-01T01:00:00+00:00 8
 
4.7%
2022-12-01T11:00:00+00:00 8
 
4.7%
2022-12-01T04:00:00+00:00 7
 
4.1%
2022-12-01T03:00:00+00:00 5
 
2.9%
2022-12-01T16:00:00+00:00 4
 
2.3%
2022-12-01T02:00:00+00:00 3
 
1.8%
Other values (16) 20
 
11.7%

Length

2023-08-13T15:45:05.894703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-01t12:00:00+00:00 69
40.4%
2022-12-01t00:00:00+00:00 24
 
14.0%
2022-12-01t17:00:00+00:00 14
 
8.2%
2022-12-01t06:00:00+00:00 9
 
5.3%
2022-12-01t01:00:00+00:00 8
 
4.7%
2022-12-01t11:00:00+00:00 8
 
4.7%
2022-12-01t04:00:00+00:00 7
 
4.1%
2022-12-01t03:00:00+00:00 5
 
2.9%
2022-12-01t16:00:00+00:00 4
 
2.3%
2022-12-02t00:00:00+00:00 3
 
1.8%
Other values (16) 20
 
11.7%

Most occurring characters

ValueCountFrequency (%)
0 1793
41.9%
2 764
17.9%
: 513
 
12.0%
1 458
 
10.7%
- 342
 
8.0%
T 171
 
4.0%
+ 171
 
4.0%
7 15
 
0.4%
6 14
 
0.3%
3 13
 
0.3%
Other values (3) 21
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3078
72.0%
Other Punctuation 513
 
12.0%
Dash Punctuation 342
 
8.0%
Uppercase Letter 171
 
4.0%
Math Symbol 171
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1793
58.3%
2 764
24.8%
1 458
 
14.9%
7 15
 
0.5%
6 14
 
0.5%
3 13
 
0.4%
5 11
 
0.4%
4 7
 
0.2%
8 3
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 513
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 171
100.0%
Math Symbol
ValueCountFrequency (%)
+ 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4104
96.0%
Latin 171
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1793
43.7%
2 764
18.6%
: 513
 
12.5%
1 458
 
11.2%
- 342
 
8.3%
+ 171
 
4.2%
7 15
 
0.4%
6 14
 
0.3%
3 13
 
0.3%
5 11
 
0.3%
Other values (2) 10
 
0.2%
Latin
ValueCountFrequency (%)
T 171
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1793
41.9%
2 764
17.9%
: 513
 
12.0%
1 458
 
10.7%
- 342
 
8.0%
T 171
 
4.0%
+ 171
 
4.0%
7 15
 
0.4%
6 14
 
0.3%
3 13
 
0.3%
Other values (3) 21
 
0.5%

runtime
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct52
Distinct (%)32.5%
Missing11
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean36.50625
Minimum2
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:05.966229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10
Q123
median31
Q347
95-th percentile60
Maximum240
Range238
Interquartile range (IQR)24

Descriptive statistics

Standard deviation25.956664
Coefficient of variation (CV)0.71101972
Kurtosis28.746689
Mean36.50625
Median Absolute Deviation (MAD)13
Skewness4.2821136
Sum5841
Variance673.74839
MonotonicityNot monotonic
2023-08-13T15:45:06.045100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 12
 
7.0%
50 11
 
6.4%
30 10
 
5.8%
44 7
 
4.1%
49 7
 
4.1%
45 7
 
4.1%
22 7
 
4.1%
10 6
 
3.5%
15 5
 
2.9%
20 5
 
2.9%
Other values (42) 83
48.5%
(Missing) 11
 
6.4%
ValueCountFrequency (%)
2 2
 
1.2%
4 1
 
0.6%
5 1
 
0.6%
7 1
 
0.6%
10 6
3.5%
11 1
 
0.6%
12 3
1.8%
14 1
 
0.6%
15 5
2.9%
16 1
 
0.6%
ValueCountFrequency (%)
240 1
 
0.6%
180 1
 
0.6%
121 1
 
0.6%
73 1
 
0.6%
69 2
1.2%
60 4
2.3%
59 1
 
0.6%
58 3
1.8%
57 3
1.8%
54 1
 
0.6%

summary
Text

MISSING 

Distinct79
Distinct (%)100.0%
Missing92
Missing (%)53.8%
Memory size1.5 KiB
2023-08-13T15:45:06.216377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length512
Median length191
Mean length188.82278
Min length40

Characters and Unicode

Total characters14917
Distinct characters78
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st row<p>Gordon's day goes from bad to worse when, distracted by the impulsive actions of an attractive stranger, Ashley, he accidentally hits a stray dog with his car.</p>
2nd row<p>When Ashley makes a mess in Gordon's sock drawer, she makes an impromptu trip to Costco with Colin, Megan and her mother, to buy Gordon some new furniture.</p>
3rd row<p>Gordon accidentally sends Ashley a dick pic and chases her from a garage sale to a death bed to try and delete it.</p>
4th row<p>Ash and Gordon's awkward sexual encounter causes them to drift apart.</p>
5th row<p>The Echo Park gang are impressed when Ashley takes charge during a power outage.</p>
ValueCountFrequency (%)
the 106
 
4.3%
to 102
 
4.1%
a 86
 
3.5%
and 83
 
3.3%
in 63
 
2.5%
of 51
 
2.1%
her 36
 
1.4%
with 25
 
1.0%
she 22
 
0.9%
is 22
 
0.9%
Other values (1183) 1888
76.0%
2023-08-13T15:45:06.490723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2403
16.1%
e 1350
 
9.1%
a 972
 
6.5%
t 970
 
6.5%
n 849
 
5.7%
o 837
 
5.6%
s 830
 
5.6%
i 816
 
5.5%
r 706
 
4.7%
h 551
 
3.7%
Other values (68) 4633
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11230
75.3%
Space Separator 2405
 
16.1%
Uppercase Letter 480
 
3.2%
Other Punctuation 428
 
2.9%
Math Symbol 324
 
2.2%
Dash Punctuation 27
 
0.2%
Decimal Number 17
 
0.1%
Close Punctuation 2
 
< 0.1%
Initial Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1350
12.0%
a 972
 
8.7%
t 970
 
8.6%
n 849
 
7.6%
o 837
 
7.5%
s 830
 
7.4%
i 816
 
7.3%
r 706
 
6.3%
h 551
 
4.9%
l 430
 
3.8%
Other values (17) 2919
26.0%
Uppercase Letter
ValueCountFrequency (%)
A 56
 
11.7%
T 47
 
9.8%
S 42
 
8.8%
L 39
 
8.1%
C 35
 
7.3%
B 24
 
5.0%
M 23
 
4.8%
W 23
 
4.8%
J 22
 
4.6%
G 22
 
4.6%
Other values (14) 147
30.6%
Other Punctuation
ValueCountFrequency (%)
. 159
37.1%
, 114
26.6%
/ 82
19.2%
' 55
 
12.9%
" 8
 
1.9%
! 4
 
0.9%
? 3
 
0.7%
; 1
 
0.2%
: 1
 
0.2%
1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 6
35.3%
6 2
 
11.8%
0 2
 
11.8%
9 2
 
11.8%
4 2
 
11.8%
1 2
 
11.8%
3 1
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 21
77.8%
4
 
14.8%
2
 
7.4%
Space Separator
ValueCountFrequency (%)
2403
99.9%
  2
 
0.1%
Math Symbol
ValueCountFrequency (%)
< 162
50.0%
> 162
50.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11710
78.5%
Common 3207
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1350
 
11.5%
a 972
 
8.3%
t 970
 
8.3%
n 849
 
7.3%
o 837
 
7.1%
s 830
 
7.1%
i 816
 
7.0%
r 706
 
6.0%
h 551
 
4.7%
l 430
 
3.7%
Other values (41) 3399
29.0%
Common
ValueCountFrequency (%)
2403
74.9%
< 162
 
5.1%
> 162
 
5.1%
. 159
 
5.0%
, 114
 
3.6%
/ 82
 
2.6%
' 55
 
1.7%
- 21
 
0.7%
" 8
 
0.2%
2 6
 
0.2%
Other values (17) 35
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14904
99.9%
Punctuation 9
 
0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2403
16.1%
e 1350
 
9.1%
a 972
 
6.5%
t 970
 
6.5%
n 849
 
5.7%
o 837
 
5.6%
s 830
 
5.6%
i 816
 
5.5%
r 706
 
4.7%
h 551
 
3.7%
Other values (62) 4620
31.0%
Punctuation
ValueCountFrequency (%)
4
44.4%
2
22.2%
2
22.2%
1
 
11.1%
None
ValueCountFrequency (%)
ñ 2
50.0%
  2
50.0%

rating.average
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)46.9%
Missing139
Missing (%)81.3%
Infinite0
Infinite (%)0.0%
Mean6.984375
Minimum3.3
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:06.576117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile6.2
Q16.575
median6.9
Q37.2
95-th percentile8.225
Maximum10
Range6.7
Interquartile range (IQR)0.625

Descriptive statistics

Standard deviation1.0314754
Coefficient of variation (CV)0.14768328
Kurtosis6.3009441
Mean6.984375
Median Absolute Deviation (MAD)0.3
Skewness-0.53410715
Sum223.5
Variance1.0639415
MonotonicityNot monotonic
2023-08-13T15:45:06.638195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
6.8 6
 
3.5%
7 5
 
2.9%
6.5 3
 
1.8%
6.2 3
 
1.8%
8 3
 
1.8%
7.1 2
 
1.2%
7.2 2
 
1.2%
7.7 1
 
0.6%
8.5 1
 
0.6%
10 1
 
0.6%
Other values (5) 5
 
2.9%
(Missing) 139
81.3%
ValueCountFrequency (%)
3.3 1
 
0.6%
6.2 3
1.8%
6.3 1
 
0.6%
6.5 3
1.8%
6.6 1
 
0.6%
6.7 1
 
0.6%
6.8 6
3.5%
7 5
2.9%
7.1 2
 
1.2%
7.2 2
 
1.2%
ValueCountFrequency (%)
10 1
 
0.6%
8.5 1
 
0.6%
8 3
1.8%
7.9 1
 
0.6%
7.7 1
 
0.6%
7.2 2
 
1.2%
7.1 2
 
1.2%
7 5
2.9%
6.8 6
3.5%
6.7 1
 
0.6%

_links.self.href
Text

UNIQUE 

Distinct171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:06.850459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6669
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2450906
2nd rowhttps://api.tvmaze.com/episodes/2450907
3rd rowhttps://api.tvmaze.com/episodes/2438114
4th rowhttps://api.tvmaze.com/episodes/2438115
5th rowhttps://api.tvmaze.com/episodes/2413779
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2450906 1
 
0.6%
https://api.tvmaze.com/episodes/2433630 1
 
0.6%
https://api.tvmaze.com/episodes/2476693 1
 
0.6%
https://api.tvmaze.com/episodes/2438114 1
 
0.6%
https://api.tvmaze.com/episodes/2438115 1
 
0.6%
https://api.tvmaze.com/episodes/2413779 1
 
0.6%
https://api.tvmaze.com/episodes/2323161 1
 
0.6%
https://api.tvmaze.com/episodes/2433627 1
 
0.6%
https://api.tvmaze.com/episodes/2433628 1
 
0.6%
https://api.tvmaze.com/episodes/2433629 1
 
0.6%
Other values (161) 161
94.2%
2023-08-13T15:45:07.151724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 684
 
10.3%
p 513
 
7.7%
s 513
 
7.7%
e 513
 
7.7%
t 513
 
7.7%
o 342
 
5.1%
a 342
 
5.1%
i 342
 
5.1%
. 342
 
5.1%
m 342
 
5.1%
Other values (16) 2223
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4275
64.1%
Other Punctuation 1197
 
17.9%
Decimal Number 1197
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 513
12.0%
s 513
12.0%
e 513
12.0%
t 513
12.0%
o 342
8.0%
a 342
8.0%
i 342
8.0%
m 342
8.0%
h 171
 
4.0%
d 171
 
4.0%
Other values (3) 513
12.0%
Decimal Number
ValueCountFrequency (%)
2 271
22.6%
4 223
18.6%
3 134
11.2%
0 98
 
8.2%
1 97
 
8.1%
5 84
 
7.0%
7 76
 
6.3%
9 74
 
6.2%
6 71
 
5.9%
8 69
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/ 684
57.1%
. 342
28.6%
: 171
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4275
64.1%
Common 2394
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 684
28.6%
. 342
14.3%
2 271
 
11.3%
4 223
 
9.3%
: 171
 
7.1%
3 134
 
5.6%
0 98
 
4.1%
1 97
 
4.1%
5 84
 
3.5%
7 76
 
3.2%
Other values (3) 214
 
8.9%
Latin
ValueCountFrequency (%)
p 513
12.0%
s 513
12.0%
e 513
12.0%
t 513
12.0%
o 342
8.0%
a 342
8.0%
i 342
8.0%
m 342
8.0%
h 171
 
4.0%
d 171
 
4.0%
Other values (3) 513
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 684
 
10.3%
p 513
 
7.7%
s 513
 
7.7%
e 513
 
7.7%
t 513
 
7.7%
o 342
 
5.1%
a 342
 
5.1%
i 342
 
5.1%
. 342
 
5.1%
m 342
 
5.1%
Other values (16) 2223
33.3%
Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:07.378516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.964912
Min length31

Characters and Unicode

Total characters5808
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)48.5%

Sample

1st rowhttps://api.tvmaze.com/shows/55724
2nd rowhttps://api.tvmaze.com/shows/55724
3rd rowhttps://api.tvmaze.com/shows/59201
4th rowhttps://api.tvmaze.com/shows/59201
5th rowhttps://api.tvmaze.com/shows/60687
ValueCountFrequency (%)
https://api.tvmaze.com/shows/64860 8
 
4.7%
https://api.tvmaze.com/shows/61880 7
 
4.1%
https://api.tvmaze.com/shows/65188 6
 
3.5%
https://api.tvmaze.com/shows/65365 6
 
3.5%
https://api.tvmaze.com/shows/60736 6
 
3.5%
https://api.tvmaze.com/shows/66150 5
 
2.9%
https://api.tvmaze.com/shows/66583 5
 
2.9%
https://api.tvmaze.com/shows/65911 4
 
2.3%
https://api.tvmaze.com/shows/67168 3
 
1.8%
https://api.tvmaze.com/shows/47633 3
 
1.8%
Other values (100) 118
69.0%
2023-08-13T15:45:07.673084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 684
 
11.8%
s 513
 
8.8%
t 513
 
8.8%
h 342
 
5.9%
p 342
 
5.9%
a 342
 
5.9%
. 342
 
5.9%
o 342
 
5.9%
m 342
 
5.9%
6 202
 
3.5%
Other values (16) 1844
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3762
64.8%
Other Punctuation 1197
 
20.6%
Decimal Number 849
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 513
13.6%
t 513
13.6%
h 342
9.1%
p 342
9.1%
a 342
9.1%
o 342
9.1%
m 342
9.1%
e 171
 
4.5%
w 171
 
4.5%
c 171
 
4.5%
Other values (3) 513
13.6%
Decimal Number
ValueCountFrequency (%)
6 202
23.8%
5 101
11.9%
4 95
11.2%
1 87
10.2%
8 82
9.7%
3 69
 
8.1%
0 62
 
7.3%
2 62
 
7.3%
7 47
 
5.5%
9 42
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 684
57.1%
. 342
28.6%
: 171
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3762
64.8%
Common 2046
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 684
33.4%
. 342
16.7%
6 202
 
9.9%
: 171
 
8.4%
5 101
 
4.9%
4 95
 
4.6%
1 87
 
4.3%
8 82
 
4.0%
3 69
 
3.4%
0 62
 
3.0%
Other values (3) 151
 
7.4%
Latin
ValueCountFrequency (%)
s 513
13.6%
t 513
13.6%
h 342
9.1%
p 342
9.1%
a 342
9.1%
o 342
9.1%
m 342
9.1%
e 171
 
4.5%
w 171
 
4.5%
c 171
 
4.5%
Other values (3) 513
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 684
 
11.8%
s 513
 
8.8%
t 513
 
8.8%
h 342
 
5.9%
p 342
 
5.9%
a 342
 
5.9%
. 342
 
5.9%
o 342
 
5.9%
m 342
 
5.9%
6 202
 
3.5%
Other values (16) 1844
31.7%

_embedded.show.id
Real number (ℝ)

HIGH CORRELATION 

Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56436.889
Minimum81
Maximum69351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:07.767525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile19670.5
Q154367.5
median63480
Q365365
95-th percentile67431
Maximum69351
Range69270
Interquartile range (IQR)10997.5

Descriptive statistics

Standard deviation15217.481
Coefficient of variation (CV)0.26963713
Kurtosis3.0606066
Mean56436.889
Median Absolute Deviation (MAD)2670
Skewness-1.9347318
Sum9650708
Variance2.3157173 × 108
MonotonicityNot monotonic
2023-08-13T15:45:07.848310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64860 8
 
4.7%
61880 7
 
4.1%
65188 6
 
3.5%
65365 6
 
3.5%
60736 6
 
3.5%
66150 5
 
2.9%
66583 5
 
2.9%
65911 4
 
2.3%
62166 3
 
1.8%
47633 3
 
1.8%
Other values (100) 118
69.0%
ValueCountFrequency (%)
81 1
0.6%
4175 1
0.6%
6220 1
0.6%
6441 1
0.6%
13215 1
0.6%
13818 2
1.2%
16753 1
0.6%
17046 1
0.6%
22295 1
0.6%
24727 1
0.6%
ValueCountFrequency (%)
69351 1
 
0.6%
69238 2
 
1.2%
68784 1
 
0.6%
68144 1
 
0.6%
67907 1
 
0.6%
67883 2
 
1.2%
67694 1
 
0.6%
67168 3
1.8%
67082 1
 
0.6%
66583 5
2.9%
Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:08.074795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length65
Mean length52.099415
Min length39

Characters and Unicode

Total characters8909
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)48.5%

Sample

1st rowhttps://www.tvmaze.com/shows/55724/hocu-vse-znat
2nd rowhttps://www.tvmaze.com/shows/55724/hocu-vse-znat
3rd rowhttps://www.tvmaze.com/shows/59201/restoran-po-ponatiam
4th rowhttps://www.tvmaze.com/shows/59201/restoran-po-ponatiam
5th rowhttps://www.tvmaze.com/shows/60687/alisa-ne-mozet-zdat
ValueCountFrequency (%)
https://www.tvmaze.com/shows/64860/colin-from-accounts 8
 
4.7%
https://www.tvmaze.com/shows/61880/zamerzsie 7
 
4.1%
https://www.tvmaze.com/shows/65188/planet-sex-with-cara-delevingne 6
 
3.5%
https://www.tvmaze.com/shows/65365/pewnego-razu-na-krajowej-jedynce 6
 
3.5%
https://www.tvmaze.com/shows/60736/the-flatshare 6
 
3.5%
https://www.tvmaze.com/shows/66150/facil 5
 
2.9%
https://www.tvmaze.com/shows/66583/neizvestnoe-budusee 5
 
2.9%
https://www.tvmaze.com/shows/65911/toxisch 4
 
2.3%
https://www.tvmaze.com/shows/67168/cocaine-prison-likes-la-vraie-histoire-disabelle 3
 
1.8%
https://www.tvmaze.com/shows/47633/tyler-perrys-bruh 3
 
1.8%
Other values (100) 118
69.0%
2023-08-13T15:45:08.468422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 855
 
9.6%
w 726
 
8.1%
s 681
 
7.6%
t 658
 
7.4%
o 525
 
5.9%
e 479
 
5.4%
h 439
 
4.9%
m 408
 
4.6%
a 401
 
4.5%
. 342
 
3.8%
Other values (30) 3395
38.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6364
71.4%
Other Punctuation 1368
 
15.4%
Decimal Number 860
 
9.7%
Dash Punctuation 317
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 726
11.4%
s 681
10.7%
t 658
10.3%
o 525
 
8.2%
e 479
 
7.5%
h 439
 
6.9%
m 408
 
6.4%
a 401
 
6.3%
c 262
 
4.1%
p 239
 
3.8%
Other values (16) 1546
24.3%
Decimal Number
ValueCountFrequency (%)
6 203
23.6%
5 101
11.7%
4 97
11.3%
1 89
10.3%
8 83
9.7%
3 69
 
8.0%
2 65
 
7.6%
0 64
 
7.4%
7 47
 
5.5%
9 42
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 855
62.5%
. 342
 
25.0%
: 171
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 317
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6364
71.4%
Common 2545
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 726
11.4%
s 681
10.7%
t 658
10.3%
o 525
 
8.2%
e 479
 
7.5%
h 439
 
6.9%
m 408
 
6.4%
a 401
 
6.3%
c 262
 
4.1%
p 239
 
3.8%
Other values (16) 1546
24.3%
Common
ValueCountFrequency (%)
/ 855
33.6%
. 342
 
13.4%
- 317
 
12.5%
6 203
 
8.0%
: 171
 
6.7%
5 101
 
4.0%
4 97
 
3.8%
1 89
 
3.5%
8 83
 
3.3%
3 69
 
2.7%
Other values (4) 218
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8909
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 855
 
9.6%
w 726
 
8.1%
s 681
 
7.6%
t 658
 
7.4%
o 525
 
5.9%
e 479
 
5.4%
h 439
 
4.9%
m 408
 
4.6%
a 401
 
4.5%
. 342
 
3.8%
Other values (30) 3395
38.1%
Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:08.676597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length30
Mean length17.385965
Min length4

Characters and Unicode

Total characters2973
Distinct characters113
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)48.5%

Sample

1st rowХочу все знать!
2nd rowХочу все знать!
3rd rowРесторан по понятиям
4th rowРесторан по понятиям
5th rowАлиса не может ждать
ValueCountFrequency (%)
the 15
 
3.1%
of 9
 
1.8%
colin 8
 
1.6%
sex 8
 
1.6%
from 8
 
1.6%
accounts 8
 
1.6%
with 7
 
1.4%
замерзшие 7
 
1.4%
planet 6
 
1.2%
cara 6
 
1.2%
Other values (274) 408
83.3%
2023-08-13T15:45:08.973765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
319
 
10.7%
e 237
 
8.0%
a 166
 
5.6%
i 150
 
5.0%
n 150
 
5.0%
o 141
 
4.7%
r 135
 
4.5%
l 112
 
3.8%
s 105
 
3.5%
t 91
 
3.1%
Other values (103) 1367
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2189
73.6%
Uppercase Letter 416
 
14.0%
Space Separator 319
 
10.7%
Other Punctuation 36
 
1.2%
Decimal Number 11
 
0.4%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 237
 
10.8%
a 166
 
7.6%
i 150
 
6.9%
n 150
 
6.9%
o 141
 
6.4%
r 135
 
6.2%
l 112
 
5.1%
s 105
 
4.8%
t 91
 
4.2%
h 72
 
3.3%
Other values (50) 830
37.9%
Uppercase Letter
ValueCountFrequency (%)
T 33
 
7.9%
C 33
 
7.9%
P 32
 
7.7%
F 28
 
6.7%
S 28
 
6.7%
D 24
 
5.8%
A 23
 
5.5%
H 22
 
5.3%
M 19
 
4.6%
L 17
 
4.1%
Other values (28) 157
37.7%
Other Punctuation
ValueCountFrequency (%)
' 12
33.3%
: 7
19.4%
! 5
13.9%
, 5
13.9%
& 4
 
11.1%
. 2
 
5.6%
# 1
 
2.8%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
4 2
18.2%
0 2
18.2%
1 2
18.2%
8 1
 
9.1%
6 1
 
9.1%
Space Separator
ValueCountFrequency (%)
319
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2199
74.0%
Cyrillic 406
 
13.7%
Common 368
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 237
 
10.8%
a 166
 
7.5%
i 150
 
6.8%
n 150
 
6.8%
o 141
 
6.4%
r 135
 
6.1%
l 112
 
5.1%
s 105
 
4.8%
t 91
 
4.1%
h 72
 
3.3%
Other values (48) 840
38.2%
Cyrillic
ValueCountFrequency (%)
е 59
 
14.5%
о 33
 
8.1%
и 26
 
6.4%
н 24
 
5.9%
а 22
 
5.4%
у 20
 
4.9%
т 20
 
4.9%
с 19
 
4.7%
р 19
 
4.7%
з 16
 
3.9%
Other values (30) 148
36.5%
Common
ValueCountFrequency (%)
319
86.7%
' 12
 
3.3%
: 7
 
1.9%
! 5
 
1.4%
, 5
 
1.4%
& 4
 
1.1%
2 3
 
0.8%
4 2
 
0.5%
0 2
 
0.5%
. 2
 
0.5%
Other values (5) 7
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2552
85.8%
Cyrillic 406
 
13.7%
None 15
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319
 
12.5%
e 237
 
9.3%
a 166
 
6.5%
i 150
 
5.9%
n 150
 
5.9%
o 141
 
5.5%
r 135
 
5.3%
l 112
 
4.4%
s 105
 
4.1%
t 91
 
3.6%
Other values (56) 946
37.1%
Cyrillic
ValueCountFrequency (%)
е 59
 
14.5%
о 33
 
8.1%
и 26
 
6.4%
н 24
 
5.9%
а 22
 
5.4%
у 20
 
4.9%
т 20
 
4.9%
с 19
 
4.7%
р 19
 
4.7%
з 16
 
3.9%
Other values (30) 148
36.5%
None
ValueCountFrequency (%)
á 5
33.3%
ï 3
20.0%
é 3
20.0%
ä 1
 
6.7%
ö 1
 
6.7%
ó 1
 
6.7%
å 1
 
6.7%

_embedded.show.type
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Scripted
97 
Documentary
20 
Animation
18 
Reality
17 
Talk Show
 
9
Other values (4)
10 

Length

Max length11
Median length8
Mean length8.3157895
Min length4

Characters and Unicode

Total characters1422
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowDocumentary
2nd rowDocumentary
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted 97
56.7%
Documentary 20
 
11.7%
Animation 18
 
10.5%
Reality 17
 
9.9%
Talk Show 9
 
5.3%
Game Show 3
 
1.8%
News 3
 
1.8%
Sports 3
 
1.8%
Variety 1
 
0.6%

Length

2023-08-13T15:45:09.070772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:09.141607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted 97
53.0%
documentary 20
 
10.9%
animation 18
 
9.8%
reality 17
 
9.3%
show 12
 
6.6%
talk 9
 
4.9%
game 3
 
1.6%
news 3
 
1.6%
sports 3
 
1.6%
variety 1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
t 156
11.0%
i 151
10.6%
e 141
9.9%
r 121
 
8.5%
c 117
 
8.2%
S 112
 
7.9%
p 100
 
7.0%
d 97
 
6.8%
a 68
 
4.8%
n 56
 
3.9%
Other values (17) 303
21.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1227
86.3%
Uppercase Letter 183
 
12.9%
Space Separator 12
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 156
12.7%
i 151
12.3%
e 141
11.5%
r 121
9.9%
c 117
9.5%
p 100
8.1%
d 97
7.9%
a 68
5.5%
n 56
 
4.6%
o 53
 
4.3%
Other values (8) 167
13.6%
Uppercase Letter
ValueCountFrequency (%)
S 112
61.2%
D 20
 
10.9%
A 18
 
9.8%
R 17
 
9.3%
T 9
 
4.9%
G 3
 
1.6%
N 3
 
1.6%
V 1
 
0.5%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1410
99.2%
Common 12
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 156
11.1%
i 151
10.7%
e 141
10.0%
r 121
8.6%
c 117
8.3%
S 112
 
7.9%
p 100
 
7.1%
d 97
 
6.9%
a 68
 
4.8%
n 56
 
4.0%
Other values (16) 291
20.6%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 156
11.0%
i 151
10.6%
e 141
9.9%
r 121
 
8.5%
c 117
 
8.2%
S 112
 
7.9%
p 100
 
7.0%
d 97
 
6.8%
a 68
 
4.8%
n 56
 
3.9%
Other values (17) 303
21.3%

_embedded.show.language
Categorical

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)10.9%
Missing6
Missing (%)3.5%
Memory size1.5 KiB
English
64 
Russian
28 
Chinese
17 
Korean
Spanish
Other values (13)
40 

Length

Max length10
Median length7
Mean length6.9454545
Min length4

Characters and Unicode

Total characters1146
Distinct characters35
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)1.8%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English 64
37.4%
Russian 28
16.4%
Chinese 17
 
9.9%
Korean 9
 
5.3%
Spanish 7
 
4.1%
Polish 6
 
3.5%
Norwegian 5
 
2.9%
German 5
 
2.9%
French 4
 
2.3%
Japanese 4
 
2.3%
Other values (8) 16
 
9.4%
(Missing) 6
 
3.5%

Length

2023-08-13T15:45:09.223169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 64
38.8%
russian 28
17.0%
chinese 17
 
10.3%
korean 9
 
5.5%
spanish 7
 
4.2%
polish 6
 
3.6%
norwegian 5
 
3.0%
german 5
 
3.0%
arabic 4
 
2.4%
japanese 4
 
2.4%
Other values (8) 16
 
9.7%

Most occurring characters

ValueCountFrequency (%)
s 159
13.9%
n 150
13.1%
i 140
12.2%
h 104
9.1%
e 74
 
6.5%
a 73
 
6.4%
l 73
 
6.4%
g 71
 
6.2%
E 64
 
5.6%
u 34
 
3.0%
Other values (25) 204
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 981
85.6%
Uppercase Letter 165
 
14.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 159
16.2%
n 150
15.3%
i 140
14.3%
h 104
10.6%
e 74
7.5%
a 73
7.4%
l 73
7.4%
g 71
7.2%
u 34
 
3.5%
r 30
 
3.1%
Other values (10) 73
7.4%
Uppercase Letter
ValueCountFrequency (%)
E 64
38.8%
R 28
17.0%
C 17
 
10.3%
S 12
 
7.3%
K 9
 
5.5%
P 8
 
4.8%
G 5
 
3.0%
N 5
 
3.0%
F 4
 
2.4%
J 4
 
2.4%
Other values (5) 9
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1146
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 159
13.9%
n 150
13.1%
i 140
12.2%
h 104
9.1%
e 74
 
6.5%
a 73
 
6.4%
l 73
 
6.4%
g 71
 
6.2%
E 64
 
5.6%
u 34
 
3.0%
Other values (25) 204
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 159
13.9%
n 150
13.1%
i 140
12.2%
h 104
9.1%
e 74
 
6.5%
a 73
 
6.4%
l 73
 
6.4%
g 71
 
6.2%
E 64
 
5.6%
u 34
 
3.0%
Other values (25) 204
17.8%

_embedded.show.genres
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.5 KiB

_embedded.show.status
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Running
78 
Ended
65 
To Be Determined
28 

Length

Max length16
Median length7
Mean length7.7134503
Min length5

Characters and Unicode

Total characters1319
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowTo Be Determined
4th rowTo Be Determined
5th rowEnded

Common Values

ValueCountFrequency (%)
Running 78
45.6%
Ended 65
38.0%
To Be Determined 28
 
16.4%

Length

2023-08-13T15:45:09.291897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:09.351201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
running 78
34.4%
ended 65
28.6%
to 28
 
12.3%
be 28
 
12.3%
determined 28
 
12.3%

Most occurring characters

ValueCountFrequency (%)
n 327
24.8%
e 177
13.4%
d 158
12.0%
i 106
 
8.0%
R 78
 
5.9%
u 78
 
5.9%
g 78
 
5.9%
E 65
 
4.9%
56
 
4.2%
T 28
 
2.1%
Other values (6) 168
12.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1036
78.5%
Uppercase Letter 227
 
17.2%
Space Separator 56
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 327
31.6%
e 177
17.1%
d 158
15.3%
i 106
 
10.2%
u 78
 
7.5%
g 78
 
7.5%
o 28
 
2.7%
t 28
 
2.7%
r 28
 
2.7%
m 28
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
R 78
34.4%
E 65
28.6%
T 28
 
12.3%
B 28
 
12.3%
D 28
 
12.3%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1263
95.8%
Common 56
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 327
25.9%
e 177
14.0%
d 158
12.5%
i 106
 
8.4%
R 78
 
6.2%
u 78
 
6.2%
g 78
 
6.2%
E 65
 
5.1%
T 28
 
2.2%
o 28
 
2.2%
Other values (5) 140
11.1%
Common
ValueCountFrequency (%)
56
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1319
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 327
24.8%
e 177
13.4%
d 158
12.0%
i 106
 
8.0%
R 78
 
5.9%
u 78
 
5.9%
g 78
 
5.9%
E 65
 
4.9%
56
 
4.2%
T 28
 
2.1%
Other values (6) 168
12.7%

_embedded.show.runtime
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)35.5%
Missing109
Missing (%)63.7%
Infinite0
Infinite (%)0.0%
Mean36.741935
Minimum2
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:09.411898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q114.25
median30
Q350
95-th percentile60
Maximum240
Range238
Interquartile range (IQR)35.75

Descriptive statistics

Standard deviation37.928723
Coefficient of variation (CV)1.0323006
Kurtosis15.674327
Mean36.741935
Median Absolute Deviation (MAD)18.5
Skewness3.4709548
Sum2278
Variance1438.588
MonotonicityNot monotonic
2023-08-13T15:45:09.478622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
50 10
 
5.8%
30 6
 
3.5%
20 6
 
3.5%
60 5
 
2.9%
10 5
 
2.9%
25 4
 
2.3%
12 3
 
1.8%
45 3
 
1.8%
15 3
 
1.8%
46 2
 
1.2%
Other values (12) 15
 
8.8%
(Missing) 109
63.7%
ValueCountFrequency (%)
2 2
 
1.2%
4 1
 
0.6%
5 2
 
1.2%
7 1
 
0.6%
10 5
2.9%
11 1
 
0.6%
12 3
1.8%
14 1
 
0.6%
15 3
1.8%
18 1
 
0.6%
ValueCountFrequency (%)
240 1
 
0.6%
180 1
 
0.6%
95 1
 
0.6%
60 5
2.9%
57 1
 
0.6%
50 10
5.8%
46 2
 
1.2%
45 3
 
1.8%
40 2
 
1.2%
30 6
3.5%

_embedded.show.averageRuntime
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)28.9%
Missing12
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean34.930818
Minimum2
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:09.551057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10
Q123
median30
Q346
95-th percentile60
Maximum215
Range213
Interquartile range (IQR)23

Descriptive statistics

Standard deviation24.487434
Coefficient of variation (CV)0.70102665
Kurtosis24.944243
Mean34.930818
Median Absolute Deviation (MAD)12
Skewness3.9417641
Sum5554
Variance599.63442
MonotonicityNot monotonic
2023-08-13T15:45:09.624671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
28 16
 
9.4%
23 14
 
8.2%
30 11
 
6.4%
49 9
 
5.3%
46 8
 
4.7%
34 8
 
4.7%
25 6
 
3.5%
15 6
 
3.5%
60 5
 
2.9%
10 5
 
2.9%
Other values (36) 71
41.5%
(Missing) 12
 
7.0%
ValueCountFrequency (%)
2 3
1.8%
4 1
 
0.6%
5 1
 
0.6%
7 1
 
0.6%
9 1
 
0.6%
10 5
2.9%
11 1
 
0.6%
12 3
1.8%
14 1
 
0.6%
15 6
3.5%
ValueCountFrequency (%)
215 1
 
0.6%
180 1
 
0.6%
98 1
 
0.6%
79 1
 
0.6%
65 1
 
0.6%
60 5
2.9%
59 1
 
0.6%
58 4
2.3%
57 3
1.8%
54 1
 
0.6%
Distinct74
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1995-10-23 00:00:00
Maximum2022-12-01 00:00:00
2023-08-13T15:45:09.699668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:09.775629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

_embedded.show.ended
Categorical

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)26.2%
Missing106
Missing (%)62.0%
Memory size1.5 KiB
2022-12-01
31 
2022-12-15
2022-12-29
2022-12-23
 
3
2022-12-03
 
3
Other values (12)
18 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters650
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)9.2%

Sample

1st row2022-12-01
2nd row2022-12-01
3rd row2022-12-01
4th row2022-12-01
5th row2022-12-01

Common Values

ValueCountFrequency (%)
2022-12-01 31
 
18.1%
2022-12-15 5
 
2.9%
2022-12-29 5
 
2.9%
2022-12-23 3
 
1.8%
2022-12-03 3
 
1.8%
2022-12-07 2
 
1.2%
2022-12-08 2
 
1.2%
2023-01-05 2
 
1.2%
2023-01-20 2
 
1.2%
2023-01-26 2
 
1.2%
Other values (7) 8
 
4.7%
(Missing) 106
62.0%

Length

2023-08-13T15:45:09.843403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-01 31
47.7%
2022-12-15 5
 
7.7%
2022-12-29 5
 
7.7%
2022-12-23 3
 
4.6%
2022-12-03 3
 
4.6%
2023-01-01 2
 
3.1%
2023-01-26 2
 
3.1%
2023-01-20 2
 
3.1%
2023-01-05 2
 
3.1%
2022-12-08 2
 
3.1%
Other values (7) 8
 
12.3%

Most occurring characters

ValueCountFrequency (%)
2 254
39.1%
- 130
20.0%
0 122
18.8%
1 103
15.8%
3 19
 
2.9%
5 8
 
1.2%
9 6
 
0.9%
7 2
 
0.3%
8 2
 
0.3%
6 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
80.0%
Dash Punctuation 130
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 254
48.8%
0 122
23.5%
1 103
19.8%
3 19
 
3.7%
5 8
 
1.5%
9 6
 
1.2%
7 2
 
0.4%
8 2
 
0.4%
6 2
 
0.4%
4 2
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 650
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 254
39.1%
- 130
20.0%
0 122
18.8%
1 103
15.8%
3 19
 
2.9%
5 8
 
1.2%
9 6
 
0.9%
7 2
 
0.3%
8 2
 
0.3%
6 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 254
39.1%
- 130
20.0%
0 122
18.8%
1 103
15.8%
3 19
 
2.9%
5 8
 
1.2%
9 6
 
0.9%
7 2
 
0.3%
8 2
 
0.3%
6 2
 
0.3%
Distinct98
Distinct (%)63.6%
Missing17
Missing (%)9.9%
Memory size1.5 KiB
2023-08-13T15:45:10.022041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length123
Median length67
Mean length47.811688
Min length17

Characters and Unicode

Total characters7363
Distinct characters75
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)47.4%

Sample

1st rowhttps://hd.kinopoisk.ru/film/4615b1810bb9c3bdb9c439fd701162a4
2nd rowhttps://hd.kinopoisk.ru/film/4615b1810bb9c3bdb9c439fd701162a4
3rd rowhttps://premier.one/show/restoran-po-ponyatiyam
4th rowhttps://premier.one/show/restoran-po-ponyatiyam
5th rowhttps://start.ru/watch/alisa-ne-mozhet-zhdat
ValueCountFrequency (%)
https://binge.com.au 8
 
5.2%
https://www.ivi.ru/watch/zamerzshie 7
 
4.5%
https://www.netflix.com/title/81442123 6
 
3.9%
https://www.bbc.co.uk/programmes/p0df24z1 6
 
3.9%
https://www.paramountplus.com/shows/the-flatshare 6
 
3.9%
https://facil.movistarplus.es 5
 
3.2%
https://www.amazon.de/toxisch/dp/b0b8rpzgm5 4
 
2.6%
https://www.bet.plus/shows/tyler-perrys-bruh 3
 
1.9%
https://www.crave.ca/en/tv-shows/cocaine-prison-likes-isabelles-true-story 3
 
1.9%
https://www.bbc.co.uk/programmes/p0db975h 3
 
1.9%
Other values (88) 103
66.9%
2023-08-13T15:45:10.315751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 663
 
9.0%
t 532
 
7.2%
s 442
 
6.0%
e 367
 
5.0%
w 317
 
4.3%
o 311
 
4.2%
h 309
 
4.2%
. 304
 
4.1%
p 302
 
4.1%
a 295
 
4.0%
Other values (65) 3521
47.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5063
68.8%
Other Punctuation 1178
 
16.0%
Decimal Number 634
 
8.6%
Uppercase Letter 331
 
4.5%
Dash Punctuation 134
 
1.8%
Math Symbol 11
 
0.1%
Connector Punctuation 10
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 532
 
10.5%
s 442
 
8.7%
e 367
 
7.2%
w 317
 
6.3%
o 311
 
6.1%
h 309
 
6.1%
p 302
 
6.0%
a 295
 
5.8%
i 248
 
4.9%
r 233
 
4.6%
Other values (16) 1707
33.7%
Uppercase Letter
ValueCountFrequency (%)
A 30
 
9.1%
P 24
 
7.3%
C 22
 
6.6%
E 21
 
6.3%
B 18
 
5.4%
S 17
 
5.1%
Z 15
 
4.5%
T 15
 
4.5%
G 15
 
4.5%
F 14
 
4.2%
Other values (16) 140
42.3%
Decimal Number
ValueCountFrequency (%)
0 101
15.9%
4 77
12.1%
2 74
11.7%
1 70
11.0%
3 59
9.3%
9 54
8.5%
8 54
8.5%
5 53
8.4%
6 51
8.0%
7 41
6.5%
Other Punctuation
ValueCountFrequency (%)
/ 663
56.3%
. 304
25.8%
: 175
 
14.9%
% 21
 
1.8%
? 10
 
0.8%
' 2
 
0.2%
& 2
 
0.2%
@ 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Math Symbol
ValueCountFrequency (%)
= 11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5394
73.3%
Common 1969
 
26.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 532
 
9.9%
s 442
 
8.2%
e 367
 
6.8%
w 317
 
5.9%
o 311
 
5.8%
h 309
 
5.7%
p 302
 
5.6%
a 295
 
5.5%
i 248
 
4.6%
r 233
 
4.3%
Other values (42) 2038
37.8%
Common
ValueCountFrequency (%)
/ 663
33.7%
. 304
15.4%
: 175
 
8.9%
- 134
 
6.8%
0 101
 
5.1%
4 77
 
3.9%
2 74
 
3.8%
1 70
 
3.6%
3 59
 
3.0%
9 54
 
2.7%
Other values (13) 258
 
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 663
 
9.0%
t 532
 
7.2%
s 442
 
6.0%
e 367
 
5.0%
w 317
 
4.3%
o 311
 
4.2%
h 309
 
4.2%
. 304
 
4.1%
p 302
 
4.1%
a 295
 
4.0%
Other values (65) 3521
47.8%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
136 
12:00
 
6
00:00
 
4
10:00
 
3
08:30
 
3
Other values (14)
19 

Length

Max length5
Median length0
Mean length1.0233918
Min length0

Characters and Unicode

Total characters175
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)5.8%

Sample

1st row
2nd row
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
136
79.5%
12:00 6
 
3.5%
00:00 4
 
2.3%
10:00 3
 
1.8%
08:30 3
 
1.8%
22:00 3
 
1.8%
17:00 2
 
1.2%
17:35 2
 
1.2%
21:00 2
 
1.2%
20:00 1
 
0.6%
Other values (9) 9
 
5.3%

Length

2023-08-13T15:45:10.406021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12:00 6
17.1%
00:00 4
11.4%
10:00 3
 
8.6%
08:30 3
 
8.6%
22:00 3
 
8.6%
17:00 2
 
5.7%
17:35 2
 
5.7%
21:00 2
 
5.7%
19:50 1
 
2.9%
19:25 1
 
2.9%
Other values (8) 8
22.9%

Most occurring characters

ValueCountFrequency (%)
0 73
41.7%
: 35
20.0%
1 22
 
12.6%
2 19
 
10.9%
3 7
 
4.0%
5 6
 
3.4%
7 5
 
2.9%
9 4
 
2.3%
8 3
 
1.7%
6 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140
80.0%
Other Punctuation 35
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 73
52.1%
1 22
 
15.7%
2 19
 
13.6%
3 7
 
5.0%
5 6
 
4.3%
7 5
 
3.6%
9 4
 
2.9%
8 3
 
2.1%
6 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
: 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 73
41.7%
: 35
20.0%
1 22
 
12.6%
2 19
 
10.9%
3 7
 
4.0%
5 6
 
3.4%
7 5
 
2.9%
9 4
 
2.3%
8 3
 
1.7%
6 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 73
41.7%
: 35
20.0%
1 22
 
12.6%
2 19
 
10.9%
3 7
 
4.0%
5 6
 
3.4%
7 5
 
2.9%
9 4
 
2.3%
8 3
 
1.7%
6 1
 
0.6%

_embedded.show.schedule.days
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.5 KiB

_embedded.show.rating.average
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)34.9%
Missing128
Missing (%)74.9%
Infinite0
Infinite (%)0.0%
Mean6.7744186
Minimum1.1
Maximum8.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:10.464447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1
5-th percentile4.58
Q15.8
median7.8
Q38
95-th percentile8.1
Maximum8.3
Range7.2
Interquartile range (IQR)2.2

Descriptive statistics

Standard deviation1.549515
Coefficient of variation (CV)0.22873033
Kurtosis3.2523044
Mean6.7744186
Median Absolute Deviation (MAD)0.5
Skewness-1.561165
Sum291.3
Variance2.4009967
MonotonicityNot monotonic
2023-08-13T15:45:10.528762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
8 10
 
5.8%
7.8 8
 
4.7%
5.8 5
 
2.9%
5.7 4
 
2.3%
8.1 2
 
1.2%
6 2
 
1.2%
6.7 2
 
1.2%
8.3 2
 
1.2%
5.4 2
 
1.2%
5.3 1
 
0.6%
Other values (5) 5
 
2.9%
(Missing) 128
74.9%
ValueCountFrequency (%)
1.1 1
 
0.6%
2.9 1
 
0.6%
4.5 1
 
0.6%
5.3 1
 
0.6%
5.4 2
 
1.2%
5.7 4
2.3%
5.8 5
2.9%
6 2
 
1.2%
6.7 2
 
1.2%
7 1
 
0.6%
ValueCountFrequency (%)
8.3 2
 
1.2%
8.1 2
 
1.2%
8 10
5.8%
7.8 8
4.7%
7.3 1
 
0.6%
7 1
 
0.6%
6.7 2
 
1.2%
6 2
 
1.2%
5.8 5
2.9%
5.7 4
 
2.3%

_embedded.show.weight
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.292398
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:10.605002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median32
Q376.5
95-th percentile95
Maximum99
Range98
Interquartile range (IQR)68.5

Descriptive statistics

Standard deviation34.318524
Coefficient of variation (CV)0.83110997
Kurtosis-1.4784625
Mean41.292398
Median Absolute Deviation (MAD)29
Skewness0.29154132
Sum7061
Variance1177.7611
MonotonicityNot monotonic
2023-08-13T15:45:10.683242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 13
 
7.6%
1 10
 
5.8%
19 9
 
5.3%
3 8
 
4.7%
2 8
 
4.7%
94 8
 
4.7%
8 6
 
3.5%
77 6
 
3.5%
67 6
 
3.5%
81 6
 
3.5%
Other values (49) 91
53.2%
ValueCountFrequency (%)
1 10
5.8%
2 8
4.7%
3 8
4.7%
4 13
7.6%
5 2
 
1.2%
8 6
3.5%
10 2
 
1.2%
11 5
 
2.9%
12 3
 
1.8%
13 2
 
1.2%
ValueCountFrequency (%)
99 3
 
1.8%
97 5
2.9%
95 2
 
1.2%
94 8
4.7%
92 1
 
0.6%
91 1
 
0.6%
87 3
 
1.8%
85 3
 
1.8%
83 1
 
0.6%
82 3
 
1.8%

_embedded.show.webChannel.id
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct56
Distinct (%)33.5%
Missing4
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean221.00599
Minimum1
Maximum552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:10.755900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.7
Q159.5
median190
Q3359
95-th percentile529
Maximum552
Range551
Interquartile range (IQR)299.5

Descriptive statistics

Standard deviation173.5992
Coefficient of variation (CV)0.78549544
Kurtosis-1.1405429
Mean221.00599
Median Absolute Deviation (MAD)161
Skewness0.37357087
Sum36908
Variance30136.681
MonotonicityNot monotonic
2023-08-13T15:45:10.829807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 17
 
9.9%
107 10
 
5.8%
26 9
 
5.3%
522 8
 
4.7%
337 7
 
4.1%
366 6
 
3.5%
104 6
 
3.5%
1 6
 
3.5%
251 5
 
2.9%
281 5
 
2.9%
Other values (46) 88
51.5%
ValueCountFrequency (%)
1 6
 
3.5%
2 2
 
1.2%
3 1
 
0.6%
12 1
 
0.6%
15 1
 
0.6%
21 17
9.9%
26 9
5.3%
30 1
 
0.6%
51 3
 
1.8%
52 1
 
0.6%
ValueCountFrequency (%)
552 1
 
0.6%
546 1
 
0.6%
541 1
 
0.6%
540 1
 
0.6%
538 3
 
1.8%
532 2
 
1.2%
522 8
4.7%
490 2
 
1.2%
482 2
 
1.2%
467 2
 
1.2%
Distinct56
Distinct (%)33.5%
Missing4
Missing (%)2.3%
Memory size1.5 KiB
2023-08-13T15:45:10.961851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.3473054
Min length3

Characters and Unicode

Total characters1227
Distinct characters68
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)15.0%

Sample

1st rowКиноПоиск HD
2nd rowКиноПоиск HD
3rd rowPremier
4th rowPremier
5th rowStart
ValueCountFrequency (%)
youtube 17
 
8.2%
paramount 10
 
4.8%
bbc 9
 
4.3%
iplayer 9
 
4.3%
binge 8
 
3.8%
ivi 7
 
3.4%
okko 6
 
2.9%
tencent 6
 
2.9%
qq 6
 
2.9%
netflix 6
 
2.9%
Other values (62) 124
59.6%
2023-08-13T15:45:11.188601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 120
 
9.8%
i 81
 
6.6%
a 73
 
5.9%
o 63
 
5.1%
u 61
 
5.0%
r 53
 
4.3%
n 49
 
4.0%
t 42
 
3.4%
T 42
 
3.4%
41
 
3.3%
Other values (58) 602
49.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 831
67.7%
Uppercase Letter 329
 
26.8%
Space Separator 41
 
3.3%
Math Symbol 23
 
1.9%
Other Punctuation 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 120
14.4%
i 81
 
9.7%
a 73
 
8.8%
o 63
 
7.6%
u 61
 
7.3%
r 53
 
6.4%
n 49
 
5.9%
t 42
 
5.1%
v 34
 
4.1%
l 33
 
4.0%
Other values (25) 222
26.7%
Uppercase Letter
ValueCountFrequency (%)
T 42
 
12.8%
B 37
 
11.2%
P 28
 
8.5%
Y 21
 
6.4%
C 18
 
5.5%
V 17
 
5.2%
Q 16
 
4.9%
N 14
 
4.3%
W 12
 
3.6%
O 12
 
3.6%
Other values (19) 112
34.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Math Symbol
ValueCountFrequency (%)
+ 23
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1102
89.8%
Common 67
 
5.5%
Cyrillic 58
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 120
 
10.9%
i 81
 
7.4%
a 73
 
6.6%
o 63
 
5.7%
u 61
 
5.5%
r 53
 
4.8%
n 49
 
4.4%
t 42
 
3.8%
T 42
 
3.8%
B 37
 
3.4%
Other values (39) 481
43.6%
Cyrillic
ValueCountFrequency (%)
о 11
19.0%
и 11
19.0%
н 6
10.3%
с 6
10.3%
К 5
8.6%
П 5
8.6%
к 5
8.6%
д 2
 
3.4%
а 1
 
1.7%
В 1
 
1.7%
Other values (5) 5
8.6%
Common
ValueCountFrequency (%)
41
61.2%
+ 23
34.3%
. 2
 
3.0%
4 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1169
95.3%
Cyrillic 58
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 120
 
10.3%
i 81
 
6.9%
a 73
 
6.2%
o 63
 
5.4%
u 61
 
5.2%
r 53
 
4.5%
n 49
 
4.2%
t 42
 
3.6%
T 42
 
3.6%
41
 
3.5%
Other values (43) 544
46.5%
Cyrillic
ValueCountFrequency (%)
о 11
19.0%
и 11
19.0%
н 6
10.3%
с 6
10.3%
К 5
8.6%
П 5
8.6%
к 5
8.6%
д 2
 
3.4%
а 1
 
1.7%
В 1
 
1.7%
Other values (5) 5
8.6%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)14.4%
Missing67
Missing (%)39.2%
Memory size1.5 KiB
Russian Federation
30 
United States
16 
China
11 
United Kingdom
10 
Australia
Other values (10)
29 

Length

Max length18
Median length14
Mean length12.365385
Min length5

Characters and Unicode

Total characters1286
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.8%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowRussian Federation
5th rowRussian Federation

Common Values

ValueCountFrequency (%)
Russian Federation 30
17.5%
United States 16
 
9.4%
China 11
 
6.4%
United Kingdom 10
 
5.8%
Australia 8
 
4.7%
Korea, Republic of 8
 
4.7%
Spain 5
 
2.9%
Canada 5
 
2.9%
Norway 3
 
1.8%
Japan 2
 
1.2%
Other values (5) 6
 
3.5%
(Missing) 67
39.2%

Length

2023-08-13T15:45:11.361021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
russian 30
17.0%
federation 30
17.0%
united 26
14.8%
states 16
9.1%
china 11
 
6.2%
kingdom 10
 
5.7%
republic 8
 
4.5%
of 8
 
4.5%
korea 8
 
4.5%
australia 8
 
4.5%
Other values (9) 21
11.9%

Most occurring characters

ValueCountFrequency (%)
a 141
11.0%
i 130
 
10.1%
e 127
 
9.9%
n 124
 
9.6%
t 97
 
7.5%
s 85
 
6.6%
d 74
 
5.8%
72
 
5.6%
o 59
 
4.6%
r 52
 
4.0%
Other values (24) 325
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1038
80.7%
Uppercase Letter 168
 
13.1%
Space Separator 72
 
5.6%
Other Punctuation 8
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 141
13.6%
i 130
12.5%
e 127
12.2%
n 124
11.9%
t 97
9.3%
s 85
8.2%
d 74
7.1%
o 59
5.7%
r 52
 
5.0%
u 47
 
4.5%
Other values (11) 102
9.8%
Uppercase Letter
ValueCountFrequency (%)
R 38
22.6%
F 30
17.9%
U 27
16.1%
S 23
13.7%
K 18
10.7%
C 16
9.5%
A 8
 
4.8%
N 4
 
2.4%
J 2
 
1.2%
B 1
 
0.6%
Space Separator
ValueCountFrequency (%)
72
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1206
93.8%
Common 80
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 141
11.7%
i 130
10.8%
e 127
10.5%
n 124
10.3%
t 97
 
8.0%
s 85
 
7.0%
d 74
 
6.1%
o 59
 
4.9%
r 52
 
4.3%
u 47
 
3.9%
Other values (22) 270
22.4%
Common
ValueCountFrequency (%)
72
90.0%
, 8
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 141
11.0%
i 130
 
10.1%
e 127
 
9.9%
n 124
 
9.6%
t 97
 
7.5%
s 85
 
6.6%
d 74
 
5.8%
72
 
5.6%
o 59
 
4.6%
r 52
 
4.0%
Other values (24) 325
25.3%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)14.4%
Missing67
Missing (%)39.2%
Memory size1.5 KiB
RU
30 
US
16 
CN
11 
GB
10 
AU
Other values (10)
29 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters208
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.8%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowRU
5th rowRU

Common Values

ValueCountFrequency (%)
RU 30
17.5%
US 16
 
9.4%
CN 11
 
6.4%
GB 10
 
5.8%
AU 8
 
4.7%
KR 8
 
4.7%
ES 5
 
2.9%
CA 5
 
2.9%
NO 3
 
1.8%
JP 2
 
1.2%
Other values (5) 6
 
3.5%
(Missing) 67
39.2%

Length

2023-08-13T15:45:11.426045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ru 30
28.8%
us 16
15.4%
cn 11
 
10.6%
gb 10
 
9.6%
au 8
 
7.7%
kr 8
 
7.7%
es 5
 
4.8%
ca 5
 
4.8%
no 3
 
2.9%
jp 2
 
1.9%
Other values (5) 6
 
5.8%

Most occurring characters

ValueCountFrequency (%)
U 55
26.4%
R 38
18.3%
S 23
11.1%
C 16
 
7.7%
N 15
 
7.2%
A 14
 
6.7%
B 11
 
5.3%
G 10
 
4.8%
E 9
 
4.3%
K 8
 
3.8%
Other values (5) 9
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 208
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 55
26.4%
R 38
18.3%
S 23
11.1%
C 16
 
7.7%
N 15
 
7.2%
A 14
 
6.7%
B 11
 
5.3%
G 10
 
4.8%
E 9
 
4.3%
K 8
 
3.8%
Other values (5) 9
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 208
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 55
26.4%
R 38
18.3%
S 23
11.1%
C 16
 
7.7%
N 15
 
7.2%
A 14
 
6.7%
B 11
 
5.3%
G 10
 
4.8%
E 9
 
4.3%
K 8
 
3.8%
Other values (5) 9
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 55
26.4%
R 38
18.3%
S 23
11.1%
C 16
 
7.7%
N 15
 
7.2%
A 14
 
6.7%
B 11
 
5.3%
G 10
 
4.8%
E 9
 
4.3%
K 8
 
3.8%
Other values (5) 9
 
4.3%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)14.4%
Missing67
Missing (%)39.2%
Memory size1.5 KiB
Asia/Kamchatka
30 
America/New_York
16 
Asia/Shanghai
11 
Europe/London
10 
Australia/Sydney
Other values (10)
29 

Length

Max length17
Median length16
Mean length13.894231
Min length10

Characters and Unicode

Total characters1445
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.8%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Kamchatka 30
17.5%
America/New_York 16
 
9.4%
Asia/Shanghai 11
 
6.4%
Europe/London 10
 
5.8%
Australia/Sydney 8
 
4.7%
Asia/Seoul 8
 
4.7%
Europe/Madrid 5
 
2.9%
America/Halifax 5
 
2.9%
Europe/Oslo 3
 
1.8%
Asia/Tokyo 2
 
1.2%
Other values (5) 6
 
3.5%
(Missing) 67
39.2%

Length

2023-08-13T15:45:11.494916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/kamchatka 30
28.8%
america/new_york 16
15.4%
asia/shanghai 11
 
10.6%
europe/london 10
 
9.6%
australia/sydney 8
 
7.7%
asia/seoul 8
 
7.7%
europe/madrid 5
 
4.8%
america/halifax 5
 
4.8%
europe/oslo 3
 
2.9%
asia/tokyo 2
 
1.9%
Other values (5) 6
 
5.8%

Most occurring characters

ValueCountFrequency (%)
a 217
15.0%
/ 104
 
7.2%
i 102
 
7.1%
A 81
 
5.6%
o 81
 
5.6%
e 81
 
5.6%
r 77
 
5.3%
s 67
 
4.6%
m 55
 
3.8%
h 55
 
3.8%
Other values (27) 525
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1101
76.2%
Uppercase Letter 224
 
15.5%
Other Punctuation 104
 
7.2%
Connector Punctuation 16
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 217
19.7%
i 102
 
9.3%
o 81
 
7.4%
e 81
 
7.4%
r 77
 
7.0%
s 67
 
6.1%
m 55
 
5.0%
h 55
 
5.0%
c 53
 
4.8%
k 50
 
4.5%
Other values (12) 263
23.9%
Uppercase Letter
ValueCountFrequency (%)
A 81
36.2%
K 30
 
13.4%
S 29
 
12.9%
E 24
 
10.7%
N 16
 
7.1%
Y 16
 
7.1%
L 10
 
4.5%
M 5
 
2.2%
H 5
 
2.2%
O 3
 
1.3%
Other values (3) 5
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1325
91.7%
Common 120
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 217
16.4%
i 102
 
7.7%
A 81
 
6.1%
o 81
 
6.1%
e 81
 
6.1%
r 77
 
5.8%
s 67
 
5.1%
m 55
 
4.2%
h 55
 
4.2%
c 53
 
4.0%
Other values (25) 456
34.4%
Common
ValueCountFrequency (%)
/ 104
86.7%
_ 16
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 217
15.0%
/ 104
 
7.2%
i 102
 
7.1%
A 81
 
5.6%
o 81
 
5.6%
e 81
 
5.6%
r 77
 
5.3%
s 67
 
4.6%
m 55
 
3.8%
h 55
 
3.8%
Other values (27) 525
36.3%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)28.0%
Missing39
Missing (%)22.8%
Memory size1.5 KiB
https://www.youtube.com
17 
https://www.paramountplus.com/
10 
https://www.bbc.co.uk/iplayer
https://binge.com.au/
 
8
https://www.ivi.ru/
 
7
Other values (32)
81 

Length

Max length41
Median length28.5
Mean length23.734848
Min length15

Characters and Unicode

Total characters3133
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)9.8%

Sample

1st rowhttps://hd.kinopoisk.ru/
2nd rowhttps://hd.kinopoisk.ru/
3rd rowhttps://www.ivi.ru/
4th rowhttps://www.ivi.ru/
5th rowhttps://www.ivi.ru/

Common Values

ValueCountFrequency (%)
https://www.youtube.com 17
 
9.9%
https://www.paramountplus.com/ 10
 
5.8%
https://www.bbc.co.uk/iplayer 9
 
5.3%
https://binge.com.au/ 8
 
4.7%
https://www.ivi.ru/ 7
 
4.1%
https://www.netflix.com/ 6
 
3.5%
https://v.qq.com/ 6
 
3.5%
https://www.max.com/ 5
 
2.9%
https://hd.kinopoisk.ru/ 5
 
2.9%
https://ver.movistarplus.es/ 5
 
2.9%
Other values (27) 54
31.6%
(Missing) 39
22.8%

Length

2023-08-13T15:45:11.568522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com 17
 
12.9%
https://www.paramountplus.com 10
 
7.6%
https://www.bbc.co.uk/iplayer 9
 
6.8%
https://binge.com.au 8
 
6.1%
https://www.ivi.ru 7
 
5.3%
https://www.netflix.com 6
 
4.5%
https://v.qq.com 6
 
4.5%
https://ver.movistarplus.es 5
 
3.8%
https://www.bet.plus 5
 
3.8%
https://www.amazon.com/adlp/freevee-about 5
 
3.8%
Other values (27) 54
40.9%

Most occurring characters

ValueCountFrequency (%)
/ 378
 
12.1%
t 334
 
10.7%
w 273
 
8.7%
. 255
 
8.1%
p 192
 
6.1%
s 180
 
5.7%
o 158
 
5.0%
h 151
 
4.8%
: 132
 
4.2%
u 117
 
3.7%
Other values (20) 963
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2362
75.4%
Other Punctuation 765
 
24.4%
Dash Punctuation 5
 
0.2%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 334
14.1%
w 273
11.6%
p 192
 
8.1%
s 180
 
7.6%
o 158
 
6.7%
h 151
 
6.4%
u 117
 
5.0%
e 117
 
5.0%
c 115
 
4.9%
m 108
 
4.6%
Other values (15) 617
26.1%
Other Punctuation
ValueCountFrequency (%)
/ 378
49.4%
. 255
33.3%
: 132
 
17.3%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2362
75.4%
Common 771
 
24.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 334
14.1%
w 273
11.6%
p 192
 
8.1%
s 180
 
7.6%
o 158
 
6.7%
h 151
 
6.4%
u 117
 
5.0%
e 117
 
5.0%
c 115
 
4.9%
m 108
 
4.6%
Other values (15) 617
26.1%
Common
ValueCountFrequency (%)
/ 378
49.0%
. 255
33.1%
: 132
 
17.1%
- 5
 
0.6%
4 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3133
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 378
 
12.1%
t 334
 
10.7%
w 273
 
8.7%
. 255
 
8.1%
p 192
 
6.1%
s 180
 
5.7%
o 158
 
5.0%
h 151
 
4.8%
: 132
 
4.2%
u 117
 
3.7%
Other values (20) 963
30.7%

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION  MISSING  UNIFORM 

Distinct2
Distinct (%)100.0%
Missing169
Missing (%)98.8%
Memory size1.5 KiB
1888.0
3171.0

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row1888.0
2nd row3171.0

Common Values

ValueCountFrequency (%)
1888.0 1
 
0.6%
3171.0 1
 
0.6%
(Missing) 169
98.8%

Length

2023-08-13T15:45:11.633120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:11.687295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1888.0 1
50.0%
3171.0 1
50.0%

Most occurring characters

ValueCountFrequency (%)
1 3
25.0%
8 3
25.0%
. 2
16.7%
0 2
16.7%
3 1
 
8.3%
7 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
83.3%
Other Punctuation 2
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
30.0%
8 3
30.0%
0 2
20.0%
3 1
 
10.0%
7 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
25.0%
8 3
25.0%
. 2
16.7%
0 2
16.7%
3 1
 
8.3%
7 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
25.0%
8 3
25.0%
. 2
16.7%
0 2
16.7%
3 1
 
8.3%
7 1
 
8.3%

_embedded.show.externals.thetvdb
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct76
Distinct (%)64.4%
Missing53
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean390833.08
Minimum75710
Maximum433942
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:11.751854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75710
5-th percentile273918.95
Q1381273
median421119.5
Q3425722
95-th percentile428075
Maximum433942
Range358232
Interquartile range (IQR)44449

Descriptive statistics

Standard deviation65710.561
Coefficient of variation (CV)0.16812948
Kurtosis11.483223
Mean390833.08
Median Absolute Deviation (MAD)6302
Skewness-3.1358906
Sum46118303
Variance4.3178778 × 109
MonotonicityNot monotonic
2023-08-13T15:45:11.831009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
421974 8
 
4.7%
418929 6
 
3.5%
425722 6
 
3.5%
426222 6
 
3.5%
423165 5
 
2.9%
428132 4
 
2.3%
381273 3
 
1.8%
427945 3
 
1.8%
325978 2
 
1.2%
367657 2
 
1.2%
Other values (66) 73
42.7%
(Missing) 53
31.0%
ValueCountFrequency (%)
75710 1
0.6%
78006 1
0.6%
83620 1
0.6%
232731 1
0.6%
248108 1
0.6%
272468 1
0.6%
274175 1
0.6%
290686 1
0.6%
296861 1
0.6%
316876 1
0.6%
ValueCountFrequency (%)
433942 1
 
0.6%
428132 4
2.3%
428075 2
1.2%
427954 1
 
0.6%
427945 3
1.8%
427796 1
 
0.6%
427575 1
 
0.6%
427268 1
 
0.6%
426929 1
 
0.6%
426466 1
 
0.6%
Distinct46
Distinct (%)55.4%
Missing88
Missing (%)51.5%
Memory size1.5 KiB
2023-08-13T15:45:11.963499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.7590361
Min length9

Characters and Unicode

Total characters810
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)39.8%

Sample

1st rowtt18228732
2nd rowtt18228732
3rd rowtt18228732
4th rowtt18228732
5th rowtt18228732
ValueCountFrequency (%)
tt18228732 8
 
9.6%
tt19723990 6
 
7.2%
tt11714672 6
 
7.2%
tt13027412 6
 
7.2%
tt20755454 5
 
6.0%
tt23834194 4
 
4.8%
tt11273012 3
 
3.6%
tt11212276 2
 
2.4%
tt8470764 2
 
2.4%
tt14760316 2
 
2.4%
Other values (36) 39
47.0%
2023-08-13T15:45:12.178671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 166
20.5%
2 108
13.3%
1 101
12.5%
4 77
9.5%
7 74
9.1%
0 66
 
8.1%
3 53
 
6.5%
8 49
 
6.0%
9 41
 
5.1%
6 40
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 644
79.5%
Lowercase Letter 166
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 108
16.8%
1 101
15.7%
4 77
12.0%
7 74
11.5%
0 66
10.2%
3 53
8.2%
8 49
7.6%
9 41
 
6.4%
6 40
 
6.2%
5 35
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
t 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 644
79.5%
Latin 166
 
20.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 108
16.8%
1 101
15.7%
4 77
12.0%
7 74
11.5%
0 66
10.2%
3 53
8.2%
8 49
7.6%
9 41
 
6.4%
6 40
 
6.2%
5 35
 
5.4%
Latin
ValueCountFrequency (%)
t 166
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 166
20.5%
2 108
13.3%
1 101
12.5%
4 77
9.5%
7 74
9.1%
0 66
 
8.1%
3 53
 
6.5%
8 49
 
6.0%
9 41
 
5.1%
6 40
 
4.9%
Distinct106
Distinct (%)65.0%
Missing8
Missing (%)4.7%
Memory size1.5 KiB
2023-08-13T15:45:12.442261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length72
Mean length71.803681
Min length70

Characters and Unicode

Total characters11704
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)49.1%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/324/812265.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/324/812265.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/391/978564.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/391/978564.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/425/1064478.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/431/1077587.jpg 8
 
4.9%
https://static.tvmaze.com/uploads/images/medium_portrait/407/1018744.jpg 7
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/431/1078946.jpg 6
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/432/1081663.jpg 6
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/444/1110324.jpg 6
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/439/1097726.jpg 5
 
3.1%
https://static.tvmaze.com/uploads/images/medium_portrait/436/1090558.jpg 4
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/449/1122658.jpg 3
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/420/1050641.jpg 3
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/432/1080062.jpg 3
 
1.8%
Other values (96) 112
68.7%
2023-08-13T15:45:12.771900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1141
 
9.7%
/ 1141
 
9.7%
m 815
 
7.0%
a 815
 
7.0%
p 652
 
5.6%
s 652
 
5.6%
i 652
 
5.6%
o 489
 
4.2%
. 489
 
4.2%
e 489
 
4.2%
Other values (22) 4369
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8150
69.6%
Other Punctuation 1793
 
15.3%
Decimal Number 1598
 
13.7%
Connector Punctuation 163
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1141
14.0%
m 815
10.0%
a 815
10.0%
p 652
 
8.0%
s 652
 
8.0%
i 652
 
8.0%
o 489
 
6.0%
e 489
 
6.0%
u 326
 
4.0%
c 326
 
4.0%
Other values (8) 1793
22.0%
Decimal Number
ValueCountFrequency (%)
1 294
18.4%
4 252
15.8%
0 192
12.0%
3 160
10.0%
7 139
8.7%
2 133
8.3%
6 116
 
7.3%
8 112
 
7.0%
9 107
 
6.7%
5 93
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/ 1141
63.6%
. 489
27.3%
: 163
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8150
69.6%
Common 3554
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1141
14.0%
m 815
10.0%
a 815
10.0%
p 652
 
8.0%
s 652
 
8.0%
i 652
 
8.0%
o 489
 
6.0%
e 489
 
6.0%
u 326
 
4.0%
c 326
 
4.0%
Other values (8) 1793
22.0%
Common
ValueCountFrequency (%)
/ 1141
32.1%
. 489
13.8%
1 294
 
8.3%
4 252
 
7.1%
0 192
 
5.4%
_ 163
 
4.6%
: 163
 
4.6%
3 160
 
4.5%
7 139
 
3.9%
2 133
 
3.7%
Other values (4) 428
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11704
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1141
 
9.7%
/ 1141
 
9.7%
m 815
 
7.0%
a 815
 
7.0%
p 652
 
5.6%
s 652
 
5.6%
i 652
 
5.6%
o 489
 
4.2%
. 489
 
4.2%
e 489
 
4.2%
Other values (22) 4369
37.3%
Distinct106
Distinct (%)65.0%
Missing8
Missing (%)4.7%
Memory size1.5 KiB
2023-08-13T15:45:13.041156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length75
Mean length74.803681
Min length73

Characters and Unicode

Total characters12193
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)49.1%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/324/812265.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/324/812265.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/391/978564.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/391/978564.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/425/1064478.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/431/1077587.jpg 8
 
4.9%
https://static.tvmaze.com/uploads/images/original_untouched/407/1018744.jpg 7
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/431/1078946.jpg 6
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/432/1081663.jpg 6
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/444/1110324.jpg 6
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/439/1097726.jpg 5
 
3.1%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090558.jpg 4
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/449/1122658.jpg 3
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/420/1050641.jpg 3
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/432/1080062.jpg 3
 
1.8%
Other values (96) 112
68.7%
2023-08-13T15:45:13.388331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1141
 
9.4%
t 978
 
8.0%
a 815
 
6.7%
s 652
 
5.3%
i 652
 
5.3%
o 652
 
5.3%
p 489
 
4.0%
c 489
 
4.0%
. 489
 
4.0%
g 489
 
4.0%
Other values (23) 5347
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8639
70.9%
Other Punctuation 1793
 
14.7%
Decimal Number 1598
 
13.1%
Connector Punctuation 163
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 978
 
11.3%
a 815
 
9.4%
s 652
 
7.5%
i 652
 
7.5%
o 652
 
7.5%
p 489
 
5.7%
c 489
 
5.7%
g 489
 
5.7%
m 489
 
5.7%
e 489
 
5.7%
Other values (9) 2445
28.3%
Decimal Number
ValueCountFrequency (%)
1 294
18.4%
4 252
15.8%
0 192
12.0%
3 160
10.0%
7 139
8.7%
2 133
8.3%
6 116
 
7.3%
8 112
 
7.0%
9 107
 
6.7%
5 93
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/ 1141
63.6%
. 489
27.3%
: 163
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8639
70.9%
Common 3554
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 978
 
11.3%
a 815
 
9.4%
s 652
 
7.5%
i 652
 
7.5%
o 652
 
7.5%
p 489
 
5.7%
c 489
 
5.7%
g 489
 
5.7%
m 489
 
5.7%
e 489
 
5.7%
Other values (9) 2445
28.3%
Common
ValueCountFrequency (%)
/ 1141
32.1%
. 489
13.8%
1 294
 
8.3%
4 252
 
7.1%
0 192
 
5.4%
: 163
 
4.6%
_ 163
 
4.6%
3 160
 
4.5%
7 139
 
3.9%
2 133
 
3.7%
Other values (4) 428
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 1141
 
9.4%
t 978
 
8.0%
a 815
 
6.7%
s 652
 
5.3%
i 652
 
5.3%
o 652
 
5.3%
p 489
 
4.0%
c 489
 
4.0%
. 489
 
4.0%
g 489
 
4.0%
Other values (23) 5347
43.9%
Distinct89
Distinct (%)66.4%
Missing37
Missing (%)21.6%
Memory size1.5 KiB
2023-08-13T15:45:13.592234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1483
Median length515
Mean length363.01493
Min length43

Characters and Unicode

Total characters48644
Distinct characters99
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)52.2%

Sample

1st row<p>Alexander Maksimov is a brilliant psychologist and the best negotiator in Russia. He has a huge experience and a large number of rescued people behind his back: he worked during terrorist attacks, persuaded hostages to be released, dissuaded criminals and victims from committing a fatal act. Over the years in the profession, Maximov has developed his own unique method of negotiating. But even a seemingly perfect employee makes mistakes. In the past, Maksimov, negotiating with terrorists who seized the school, is defeated — his daughter is killed. Unable to look into the eyes of his wife and son, Alexander leaves the family. Years later, the hero again encounters the culprit of that tragedy — it turns out that the attacker did not die during the explosion at that school and now throws Maximov a new challenge.</p>
2nd row<p>Centred on Ashley and Gordon, two single(ish), complex humans who are brought together by a car accident and an injured dog, <b>Colin from Accounts</b> is about flawed, funny people choosing each other and being brave enough to show their true self, scars and all, as they navigate life together.</p>
3rd row<p>Centred on Ashley and Gordon, two single(ish), complex humans who are brought together by a car accident and an injured dog, <b>Colin from Accounts</b> is about flawed, funny people choosing each other and being brave enough to show their true self, scars and all, as they navigate life together.</p>
4th row<p>Centred on Ashley and Gordon, two single(ish), complex humans who are brought together by a car accident and an injured dog, <b>Colin from Accounts</b> is about flawed, funny people choosing each other and being brave enough to show their true self, scars and all, as they navigate life together.</p>
5th row<p>Centred on Ashley and Gordon, two single(ish), complex humans who are brought together by a car accident and an injured dog, <b>Colin from Accounts</b> is about flawed, funny people choosing each other and being brave enough to show their true self, scars and all, as they navigate life together.</p>
ValueCountFrequency (%)
the 345
 
4.3%
and 294
 
3.7%
to 216
 
2.7%
a 210
 
2.6%
of 193
 
2.4%
in 146
 
1.8%
is 92
 
1.2%
on 85
 
1.1%
her 77
 
1.0%
their 73
 
0.9%
Other values (2113) 6266
78.4%
2023-08-13T15:45:13.905213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7852
16.1%
e 4682
 
9.6%
t 3031
 
6.2%
a 2976
 
6.1%
n 2852
 
5.9%
o 2773
 
5.7%
i 2669
 
5.5%
r 2467
 
5.1%
s 2439
 
5.0%
h 1957
 
4.0%
Other values (89) 14946
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37240
76.6%
Space Separator 7863
 
16.2%
Other Punctuation 1288
 
2.6%
Uppercase Letter 1282
 
2.6%
Math Symbol 786
 
1.6%
Dash Punctuation 82
 
0.2%
Decimal Number 74
 
0.2%
Close Punctuation 12
 
< 0.1%
Open Punctuation 12
 
< 0.1%
Initial Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4682
12.6%
t 3031
 
8.1%
a 2976
 
8.0%
n 2852
 
7.7%
o 2773
 
7.4%
i 2669
 
7.2%
r 2467
 
6.6%
s 2439
 
6.5%
h 1957
 
5.3%
l 1577
 
4.2%
Other values (28) 9817
26.4%
Uppercase Letter
ValueCountFrequency (%)
T 137
 
10.7%
A 109
 
8.5%
C 98
 
7.6%
S 91
 
7.1%
W 63
 
4.9%
L 63
 
4.9%
B 60
 
4.7%
H 60
 
4.7%
J 58
 
4.5%
Y 55
 
4.3%
Other values (16) 488
38.1%
Other Punctuation
ValueCountFrequency (%)
, 502
39.0%
. 391
30.4%
/ 204
15.8%
' 125
 
9.7%
" 19
 
1.5%
? 17
 
1.3%
: 10
 
0.8%
; 9
 
0.7%
! 5
 
0.4%
3
 
0.2%
Other values (2) 3
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 16
21.6%
2 15
20.3%
1 12
16.2%
6 7
9.5%
4 7
9.5%
5 5
 
6.8%
9 4
 
5.4%
3 4
 
5.4%
8 2
 
2.7%
7 2
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 68
82.9%
10
 
12.2%
4
 
4.9%
Space Separator
ValueCountFrequency (%)
7852
99.9%
  11
 
0.1%
Math Symbol
ValueCountFrequency (%)
< 393
50.0%
> 393
50.0%
Close Punctuation
ValueCountFrequency (%)
) 11
91.7%
] 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 11
91.7%
[ 1
 
8.3%
Initial Punctuation
ValueCountFrequency (%)
4
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38514
79.2%
Common 10122
 
20.8%
Cyrillic 8
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4682
12.2%
t 3031
 
7.9%
a 2976
 
7.7%
n 2852
 
7.4%
o 2773
 
7.2%
i 2669
 
6.9%
r 2467
 
6.4%
s 2439
 
6.3%
h 1957
 
5.1%
l 1577
 
4.1%
Other values (47) 11091
28.8%
Common
ValueCountFrequency (%)
7852
77.6%
, 502
 
5.0%
< 393
 
3.9%
> 393
 
3.9%
. 391
 
3.9%
/ 204
 
2.0%
' 125
 
1.2%
- 68
 
0.7%
" 19
 
0.2%
? 17
 
0.2%
Other values (25) 158
 
1.6%
Cyrillic
ValueCountFrequency (%)
и 2
25.0%
т 1
12.5%
д 1
12.5%
о 1
12.5%
п 1
12.5%
н 1
12.5%
А 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48582
99.9%
None 33
 
0.1%
Punctuation 21
 
< 0.1%
Cyrillic 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7852
16.2%
e 4682
 
9.6%
t 3031
 
6.2%
a 2976
 
6.1%
n 2852
 
5.9%
o 2773
 
5.7%
i 2669
 
5.5%
r 2467
 
5.1%
s 2439
 
5.0%
h 1957
 
4.0%
Other values (71) 14884
30.6%
None
ValueCountFrequency (%)
  11
33.3%
é 10
30.3%
á 5
15.2%
ö 3
 
9.1%
í 2
 
6.1%
å 1
 
3.0%
ä 1
 
3.0%
Punctuation
ValueCountFrequency (%)
10
47.6%
4
 
19.0%
4
 
19.0%
3
 
14.3%
Cyrillic
ValueCountFrequency (%)
и 2
25.0%
т 1
12.5%
д 1
12.5%
о 1
12.5%
п 1
12.5%
н 1
12.5%
А 1
12.5%

_embedded.show.updated
Real number (ℝ)

HIGH CORRELATION 

Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6803126 × 109
Minimum1.6680061 × 109
Maximum1.6918322 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:14.004700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6680061 × 109
5-th percentile1.6707019 × 109
Q11.6727532 × 109
median1.6796917 × 109
Q31.6871324 × 109
95-th percentile1.6912951 × 109
Maximum1.6918322 × 109
Range23826131
Interquartile range (IQR)14379280

Descriptive statistics

Standard deviation7503392.3
Coefficient of variation (CV)0.004465474
Kurtosis-1.5123215
Mean1.6803126 × 109
Median Absolute Deviation (MAD)7231555
Skewness0.12817104
Sum2.8733346 × 1011
Variance5.6300896 × 1013
MonotonicityNot monotonic
2023-08-13T15:45:14.083926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1691295111 8
 
4.7%
1676360040 7
 
4.1%
1687132439 6
 
3.5%
1670701938 6
 
3.5%
1674881954 6
 
3.5%
1672753159 5
 
2.9%
1674373758 5
 
2.9%
1671826084 4
 
2.3%
1670770136 3
 
1.8%
1689534070 3
 
1.8%
Other values (100) 118
69.0%
ValueCountFrequency (%)
1668006079 1
 
0.6%
1668909458 1
 
0.6%
1669792539 2
 
1.2%
1670179582 1
 
0.6%
1670701938 6
3.5%
1670770136 3
1.8%
1671103265 2
 
1.2%
1671145059 1
 
0.6%
1671145408 2
 
1.2%
1671146775 1
 
0.6%
ValueCountFrequency (%)
1691832210 1
 
0.6%
1691759897 1
 
0.6%
1691736532 1
 
0.6%
1691704239 1
 
0.6%
1691694467 1
 
0.6%
1691570800 1
 
0.6%
1691421062 1
 
0.6%
1691295111 8
4.7%
1691256868 1
 
0.6%
1691146974 1
 
0.6%
Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:14.289074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.964912
Min length31

Characters and Unicode

Total characters5808
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)48.5%

Sample

1st rowhttps://api.tvmaze.com/shows/55724
2nd rowhttps://api.tvmaze.com/shows/55724
3rd rowhttps://api.tvmaze.com/shows/59201
4th rowhttps://api.tvmaze.com/shows/59201
5th rowhttps://api.tvmaze.com/shows/60687
ValueCountFrequency (%)
https://api.tvmaze.com/shows/64860 8
 
4.7%
https://api.tvmaze.com/shows/61880 7
 
4.1%
https://api.tvmaze.com/shows/65188 6
 
3.5%
https://api.tvmaze.com/shows/65365 6
 
3.5%
https://api.tvmaze.com/shows/60736 6
 
3.5%
https://api.tvmaze.com/shows/66150 5
 
2.9%
https://api.tvmaze.com/shows/66583 5
 
2.9%
https://api.tvmaze.com/shows/65911 4
 
2.3%
https://api.tvmaze.com/shows/67168 3
 
1.8%
https://api.tvmaze.com/shows/47633 3
 
1.8%
Other values (100) 118
69.0%
2023-08-13T15:45:14.584243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 684
 
11.8%
s 513
 
8.8%
t 513
 
8.8%
h 342
 
5.9%
p 342
 
5.9%
a 342
 
5.9%
. 342
 
5.9%
o 342
 
5.9%
m 342
 
5.9%
6 202
 
3.5%
Other values (16) 1844
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3762
64.8%
Other Punctuation 1197
 
20.6%
Decimal Number 849
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 513
13.6%
t 513
13.6%
h 342
9.1%
p 342
9.1%
a 342
9.1%
o 342
9.1%
m 342
9.1%
e 171
 
4.5%
w 171
 
4.5%
c 171
 
4.5%
Other values (3) 513
13.6%
Decimal Number
ValueCountFrequency (%)
6 202
23.8%
5 101
11.9%
4 95
11.2%
1 87
10.2%
8 82
9.7%
3 69
 
8.1%
0 62
 
7.3%
2 62
 
7.3%
7 47
 
5.5%
9 42
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 684
57.1%
. 342
28.6%
: 171
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3762
64.8%
Common 2046
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 684
33.4%
. 342
16.7%
6 202
 
9.9%
: 171
 
8.4%
5 101
 
4.9%
4 95
 
4.6%
1 87
 
4.3%
8 82
 
4.0%
3 69
 
3.4%
0 62
 
3.0%
Other values (3) 151
 
7.4%
Latin
ValueCountFrequency (%)
s 513
13.6%
t 513
13.6%
h 342
9.1%
p 342
9.1%
a 342
9.1%
o 342
9.1%
m 342
9.1%
e 171
 
4.5%
w 171
 
4.5%
c 171
 
4.5%
Other values (3) 513
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 684
 
11.8%
s 513
 
8.8%
t 513
 
8.8%
h 342
 
5.9%
p 342
 
5.9%
a 342
 
5.9%
. 342
 
5.9%
o 342
 
5.9%
m 342
 
5.9%
6 202
 
3.5%
Other values (16) 1844
31.7%
Distinct110
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:14.843007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters6669
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)48.5%

Sample

1st rowhttps://api.tvmaze.com/episodes/2575700
2nd rowhttps://api.tvmaze.com/episodes/2575700
3rd rowhttps://api.tvmaze.com/episodes/2438121
4th rowhttps://api.tvmaze.com/episodes/2438121
5th rowhttps://api.tvmaze.com/episodes/2413779
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2422016 8
 
4.7%
https://api.tvmaze.com/episodes/2433632 7
 
4.1%
https://api.tvmaze.com/episodes/2430806 6
 
3.5%
https://api.tvmaze.com/episodes/2440594 6
 
3.5%
https://api.tvmaze.com/episodes/2433977 6
 
3.5%
https://api.tvmaze.com/episodes/2461025 5
 
2.9%
https://api.tvmaze.com/episodes/2476697 5
 
2.9%
https://api.tvmaze.com/episodes/2452720 4
 
2.3%
https://api.tvmaze.com/episodes/2495539 3
 
1.8%
https://api.tvmaze.com/episodes/2597955 3
 
1.8%
Other values (100) 118
69.0%
2023-08-13T15:45:15.166936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 684
 
10.3%
p 513
 
7.7%
s 513
 
7.7%
e 513
 
7.7%
t 513
 
7.7%
o 342
 
5.1%
a 342
 
5.1%
i 342
 
5.1%
. 342
 
5.1%
m 342
 
5.1%
Other values (16) 2223
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4275
64.1%
Other Punctuation 1197
 
17.9%
Decimal Number 1197
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 513
12.0%
s 513
12.0%
e 513
12.0%
t 513
12.0%
o 342
8.0%
a 342
8.0%
i 342
8.0%
m 342
8.0%
h 171
 
4.0%
d 171
 
4.0%
Other values (3) 513
12.0%
Decimal Number
ValueCountFrequency (%)
2 274
22.9%
4 189
15.8%
5 133
11.1%
3 123
10.3%
0 99
 
8.3%
6 82
 
6.9%
9 81
 
6.8%
7 81
 
6.8%
1 72
 
6.0%
8 63
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/ 684
57.1%
. 342
28.6%
: 171
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4275
64.1%
Common 2394
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 684
28.6%
. 342
14.3%
2 274
11.4%
4 189
 
7.9%
: 171
 
7.1%
5 133
 
5.6%
3 123
 
5.1%
0 99
 
4.1%
6 82
 
3.4%
9 81
 
3.4%
Other values (3) 216
 
9.0%
Latin
ValueCountFrequency (%)
p 513
12.0%
s 513
12.0%
e 513
12.0%
t 513
12.0%
o 342
8.0%
a 342
8.0%
i 342
8.0%
m 342
8.0%
h 171
 
4.0%
d 171
 
4.0%
Other values (3) 513
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 684
 
10.3%
p 513
 
7.7%
s 513
 
7.7%
e 513
 
7.7%
t 513
 
7.7%
o 342
 
5.1%
a 342
 
5.1%
i 342
 
5.1%
. 342
 
5.1%
m 342
 
5.1%
Other values (16) 2223
33.3%

image.medium
Text

MISSING 

Distinct80
Distinct (%)100.0%
Missing91
Missing (%)53.2%
Memory size1.5 KiB
2023-08-13T15:45:15.496338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters5840
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/432/1081693.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/433/1084040.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/433/1084095.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/433/1082878.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/433/1084090.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/432/1081736.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/434/1085583.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1084040.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1084095.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1082878.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1084090.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1084089.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1082867.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1084088.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/433/1082868.jpg 1
 
1.2%
Other values (70) 70
87.5%
2023-08-13T15:45:15.885238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 560
 
9.6%
a 480
 
8.2%
t 400
 
6.8%
s 400
 
6.8%
m 400
 
6.8%
p 320
 
5.5%
e 320
 
5.5%
. 240
 
4.1%
c 240
 
4.1%
d 240
 
4.1%
Other values (22) 2240
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4080
69.9%
Other Punctuation 880
 
15.1%
Decimal Number 800
 
13.7%
Connector Punctuation 80
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 480
11.8%
t 400
9.8%
s 400
9.8%
m 400
9.8%
p 320
 
7.8%
e 320
 
7.8%
c 240
 
5.9%
d 240
 
5.9%
i 240
 
5.9%
g 160
 
3.9%
Other values (8) 880
21.6%
Decimal Number
ValueCountFrequency (%)
4 137
17.1%
1 135
16.9%
3 112
14.0%
0 105
13.1%
8 90
11.2%
9 61
7.6%
2 51
 
6.4%
5 44
 
5.5%
7 35
 
4.4%
6 30
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 560
63.6%
. 240
27.3%
: 80
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4080
69.9%
Common 1760
30.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 480
11.8%
t 400
9.8%
s 400
9.8%
m 400
9.8%
p 320
 
7.8%
e 320
 
7.8%
c 240
 
5.9%
d 240
 
5.9%
i 240
 
5.9%
g 160
 
3.9%
Other values (8) 880
21.6%
Common
ValueCountFrequency (%)
/ 560
31.8%
. 240
13.6%
4 137
 
7.8%
1 135
 
7.7%
3 112
 
6.4%
0 105
 
6.0%
8 90
 
5.1%
_ 80
 
4.5%
: 80
 
4.5%
9 61
 
3.5%
Other values (4) 160
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 560
 
9.6%
a 480
 
8.2%
t 400
 
6.8%
s 400
 
6.8%
m 400
 
6.8%
p 320
 
5.5%
e 320
 
5.5%
. 240
 
4.1%
c 240
 
4.1%
d 240
 
4.1%
Other values (22) 2240
38.4%

image.original
Text

MISSING 

Distinct80
Distinct (%)100.0%
Missing91
Missing (%)53.2%
Memory size1.5 KiB
2023-08-13T15:45:16.227084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters6000
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/432/1081693.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/433/1084040.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/433/1084095.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/433/1082878.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/433/1084090.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/432/1081736.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/434/1085583.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1084040.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1084095.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1082878.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1084090.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1084089.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1082867.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1084088.jpg 1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/433/1082868.jpg 1
 
1.2%
Other values (70) 70
87.5%
2023-08-13T15:45:16.625960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 560
 
9.3%
t 480
 
8.0%
a 400
 
6.7%
s 320
 
5.3%
i 320
 
5.3%
o 320
 
5.3%
p 240
 
4.0%
c 240
 
4.0%
. 240
 
4.0%
g 240
 
4.0%
Other values (23) 2640
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4240
70.7%
Other Punctuation 880
 
14.7%
Decimal Number 800
 
13.3%
Connector Punctuation 80
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 480
 
11.3%
a 400
 
9.4%
s 320
 
7.5%
i 320
 
7.5%
o 320
 
7.5%
p 240
 
5.7%
c 240
 
5.7%
g 240
 
5.7%
m 240
 
5.7%
e 240
 
5.7%
Other values (9) 1200
28.3%
Decimal Number
ValueCountFrequency (%)
4 137
17.1%
1 135
16.9%
3 112
14.0%
0 105
13.1%
8 90
11.2%
9 61
7.6%
2 51
 
6.4%
5 44
 
5.5%
7 35
 
4.4%
6 30
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 560
63.6%
. 240
27.3%
: 80
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4240
70.7%
Common 1760
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 480
 
11.3%
a 400
 
9.4%
s 320
 
7.5%
i 320
 
7.5%
o 320
 
7.5%
p 240
 
5.7%
c 240
 
5.7%
g 240
 
5.7%
m 240
 
5.7%
e 240
 
5.7%
Other values (9) 1200
28.3%
Common
ValueCountFrequency (%)
/ 560
31.8%
. 240
13.6%
4 137
 
7.8%
1 135
 
7.7%
3 112
 
6.4%
0 105
 
6.0%
8 90
 
5.1%
: 80
 
4.5%
_ 80
 
4.5%
9 61
 
3.5%
Other values (4) 160
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 560
 
9.3%
t 480
 
8.0%
a 400
 
6.7%
s 320
 
5.3%
i 320
 
5.3%
o 320
 
5.3%
p 240
 
4.0%
c 240
 
4.0%
. 240
 
4.0%
g 240
 
4.0%
Other values (23) 2640
44.0%

_embedded.show.network.id
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)54.5%
Missing149
Missing (%)87.1%
Infinite0
Infinite (%)0.0%
Mean441.09091
Minimum78
Maximum1366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-08-13T15:45:16.707568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum78
5-th percentile80.5
Q1264
median270
Q3514
95-th percentile1355.4
Maximum1366
Range1288
Interquartile range (IQR)250

Descriptive statistics

Standard deviation384.96393
Coefficient of variation (CV)0.87275418
Kurtosis1.6998117
Mean441.09091
Median Absolute Deviation (MAD)140.5
Skewness1.6144441
Sum9704
Variance148197.23
MonotonicityNot monotonic
2023-08-13T15:45:16.767788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
270 8
 
4.7%
514 2
 
1.2%
78 2
 
1.2%
1366 2
 
1.2%
1154 1
 
0.6%
128 1
 
0.6%
262 1
 
0.6%
131 1
 
0.6%
205 1
 
0.6%
739 1
 
0.6%
Other values (2) 2
 
1.2%
(Missing) 149
87.1%
ValueCountFrequency (%)
78 2
 
1.2%
128 1
 
0.6%
131 1
 
0.6%
205 1
 
0.6%
262 1
 
0.6%
270 8
4.7%
451 1
 
0.6%
514 2
 
1.2%
558 1
 
0.6%
739 1
 
0.6%
ValueCountFrequency (%)
1366 2
 
1.2%
1154 1
 
0.6%
739 1
 
0.6%
558 1
 
0.6%
514 2
 
1.2%
451 1
 
0.6%
270 8
4.7%
262 1
 
0.6%
205 1
 
0.6%
131 1
 
0.6%
Distinct12
Distinct (%)54.5%
Missing149
Missing (%)87.1%
Memory size1.5 KiB
2023-08-13T15:45:16.857816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length9.7727273
Min length3

Characters and Unicode

Total characters215
Distinct characters40
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)36.4%

Sample

1st rowFox Showcase
2nd rowFox Showcase
3rd rowFox Showcase
4th rowFox Showcase
5th rowFox Showcase
ValueCountFrequency (%)
fox 8
20.5%
showcase 8
20.5%
тв-3 2
 
5.1%
disney 2
 
5.1%
channel 2
 
5.1%
mtv 2
 
5.1%
brasil 2
 
5.1%
nfl 1
 
2.6%
radio-canada 1
 
2.6%
ici 1
 
2.6%
Other values (10) 10
25.6%
2023-08-13T15:45:17.040356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 18
 
8.4%
17
 
7.9%
a 16
 
7.4%
e 13
 
6.0%
s 12
 
5.6%
S 11
 
5.1%
F 10
 
4.7%
h 10
 
4.7%
w 9
 
4.2%
c 8
 
3.7%
Other values (30) 91
42.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 125
58.1%
Uppercase Letter 65
30.2%
Space Separator 17
 
7.9%
Decimal Number 5
 
2.3%
Dash Punctuation 3
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 18
14.4%
a 16
12.8%
e 13
10.4%
s 12
9.6%
h 10
8.0%
w 9
7.2%
c 8
6.4%
x 8
6.4%
n 7
 
5.6%
i 6
 
4.8%
Other values (9) 18
14.4%
Uppercase Letter
ValueCountFrequency (%)
S 11
16.9%
F 10
15.4%
V 6
9.2%
T 6
9.2%
B 5
7.7%
C 5
7.7%
I 3
 
4.6%
M 3
 
4.6%
D 3
 
4.6%
K 3
 
4.6%
Other values (6) 10
15.4%
Decimal Number
ValueCountFrequency (%)
3 3
60.0%
1 1
 
20.0%
2 1
 
20.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 186
86.5%
Common 25
 
11.6%
Cyrillic 4
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 18
 
9.7%
a 16
 
8.6%
e 13
 
7.0%
s 12
 
6.5%
S 11
 
5.9%
F 10
 
5.4%
h 10
 
5.4%
w 9
 
4.8%
c 8
 
4.3%
x 8
 
4.3%
Other values (23) 71
38.2%
Common
ValueCountFrequency (%)
17
68.0%
3 3
 
12.0%
- 3
 
12.0%
1 1
 
4.0%
2 1
 
4.0%
Cyrillic
ValueCountFrequency (%)
Т 2
50.0%
В 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 209
97.2%
Cyrillic 4
 
1.9%
None 2
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 18
 
8.6%
17
 
8.1%
a 16
 
7.7%
e 13
 
6.2%
s 12
 
5.7%
S 11
 
5.3%
F 10
 
4.8%
h 10
 
4.8%
w 9
 
4.3%
c 8
 
3.8%
Other values (27) 85
40.7%
None
ValueCountFrequency (%)
é 2
100.0%
Cyrillic
ValueCountFrequency (%)
Т 2
50.0%
В 2
50.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)36.4%
Missing149
Missing (%)87.1%
Memory size1.5 KiB
Australia
United States
Russian Federation
Korea, Republic of
Brazil
Other values (3)

Length

Max length18
Median length13
Mean length10.636364
Min length5

Characters and Unicode

Total characters234
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st rowAustralia
2nd rowAustralia
3rd rowAustralia
4th rowAustralia
5th rowAustralia

Common Values

ValueCountFrequency (%)
Australia 9
 
5.3%
United States 4
 
2.3%
Russian Federation 2
 
1.2%
Korea, Republic of 2
 
1.2%
Brazil 2
 
1.2%
Japan 1
 
0.6%
Sweden 1
 
0.6%
Canada 1
 
0.6%
(Missing) 149
87.1%

Length

2023-08-13T15:45:17.127380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:17.195697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
australia 9
28.1%
united 4
12.5%
states 4
12.5%
russian 2
 
6.2%
federation 2
 
6.2%
korea 2
 
6.2%
republic 2
 
6.2%
of 2
 
6.2%
brazil 2
 
6.2%
japan 1
 
3.1%
Other values (2) 2
 
6.2%

Most occurring characters

ValueCountFrequency (%)
a 35
15.0%
t 23
 
9.8%
i 21
 
9.0%
e 18
 
7.7%
s 17
 
7.3%
r 15
 
6.4%
u 13
 
5.6%
l 13
 
5.6%
n 11
 
4.7%
10
 
4.3%
Other values (18) 58
24.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192
82.1%
Uppercase Letter 30
 
12.8%
Space Separator 10
 
4.3%
Other Punctuation 2
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 35
18.2%
t 23
12.0%
i 21
10.9%
e 18
9.4%
s 17
8.9%
r 15
7.8%
u 13
 
6.8%
l 13
 
6.8%
n 11
 
5.7%
d 8
 
4.2%
Other values (7) 18
9.4%
Uppercase Letter
ValueCountFrequency (%)
A 9
30.0%
S 5
16.7%
R 4
13.3%
U 4
13.3%
F 2
 
6.7%
K 2
 
6.7%
B 2
 
6.7%
J 1
 
3.3%
C 1
 
3.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 222
94.9%
Common 12
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 35
15.8%
t 23
10.4%
i 21
9.5%
e 18
 
8.1%
s 17
 
7.7%
r 15
 
6.8%
u 13
 
5.9%
l 13
 
5.9%
n 11
 
5.0%
A 9
 
4.1%
Other values (16) 47
21.2%
Common
ValueCountFrequency (%)
10
83.3%
, 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 35
15.0%
t 23
 
9.8%
i 21
 
9.0%
e 18
 
7.7%
s 17
 
7.3%
r 15
 
6.4%
u 13
 
5.6%
l 13
 
5.6%
n 11
 
4.7%
10
 
4.3%
Other values (18) 58
24.8%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)36.4%
Missing149
Missing (%)87.1%
Memory size1.5 KiB
AU
US
RU
KR
BR
Other values (3)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters44
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st rowAU
2nd rowAU
3rd rowAU
4th rowAU
5th rowAU

Common Values

ValueCountFrequency (%)
AU 9
 
5.3%
US 4
 
2.3%
RU 2
 
1.2%
KR 2
 
1.2%
BR 2
 
1.2%
JP 1
 
0.6%
SE 1
 
0.6%
CA 1
 
0.6%
(Missing) 149
87.1%

Length

2023-08-13T15:45:17.268807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:17.333485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
au 9
40.9%
us 4
18.2%
ru 2
 
9.1%
kr 2
 
9.1%
br 2
 
9.1%
jp 1
 
4.5%
se 1
 
4.5%
ca 1
 
4.5%

Most occurring characters

ValueCountFrequency (%)
U 15
34.1%
A 10
22.7%
R 6
 
13.6%
S 5
 
11.4%
K 2
 
4.5%
B 2
 
4.5%
J 1
 
2.3%
P 1
 
2.3%
E 1
 
2.3%
C 1
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 44
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 15
34.1%
A 10
22.7%
R 6
 
13.6%
S 5
 
11.4%
K 2
 
4.5%
B 2
 
4.5%
J 1
 
2.3%
P 1
 
2.3%
E 1
 
2.3%
C 1
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 44
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 15
34.1%
A 10
22.7%
R 6
 
13.6%
S 5
 
11.4%
K 2
 
4.5%
B 2
 
4.5%
J 1
 
2.3%
P 1
 
2.3%
E 1
 
2.3%
C 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 15
34.1%
A 10
22.7%
R 6
 
13.6%
S 5
 
11.4%
K 2
 
4.5%
B 2
 
4.5%
J 1
 
2.3%
P 1
 
2.3%
E 1
 
2.3%
C 1
 
2.3%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)36.4%
Missing149
Missing (%)87.1%
Memory size1.5 KiB
Australia/Sydney
America/New_York
Asia/Kamchatka
Asia/Seoul
America/Noronha
Other values (3)

Length

Max length16
Median length16
Mean length14.863636
Min length10

Characters and Unicode

Total characters327
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st rowAustralia/Sydney
2nd rowAustralia/Sydney
3rd rowAustralia/Sydney
4th rowAustralia/Sydney
5th rowAustralia/Sydney

Common Values

ValueCountFrequency (%)
Australia/Sydney 9
 
5.3%
America/New_York 4
 
2.3%
Asia/Kamchatka 2
 
1.2%
Asia/Seoul 2
 
1.2%
America/Noronha 2
 
1.2%
Asia/Tokyo 1
 
0.6%
Europe/Stockholm 1
 
0.6%
America/Halifax 1
 
0.6%
(Missing) 149
87.1%

Length

2023-08-13T15:45:17.410542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:17.481734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
australia/sydney 9
40.9%
america/new_york 4
18.2%
asia/kamchatka 2
 
9.1%
asia/seoul 2
 
9.1%
america/noronha 2
 
9.1%
asia/tokyo 1
 
4.5%
europe/stockholm 1
 
4.5%
america/halifax 1
 
4.5%

Most occurring characters

ValueCountFrequency (%)
a 40
 
12.2%
r 23
 
7.0%
e 23
 
7.0%
i 22
 
6.7%
/ 22
 
6.7%
A 21
 
6.4%
y 19
 
5.8%
o 15
 
4.6%
s 14
 
4.3%
l 13
 
4.0%
Other values (20) 115
35.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 253
77.4%
Uppercase Letter 48
 
14.7%
Other Punctuation 22
 
6.7%
Connector Punctuation 4
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 40
15.8%
r 23
 
9.1%
e 23
 
9.1%
i 22
 
8.7%
y 19
 
7.5%
o 15
 
5.9%
s 14
 
5.5%
l 13
 
5.1%
u 12
 
4.7%
t 12
 
4.7%
Other values (10) 60
23.7%
Uppercase Letter
ValueCountFrequency (%)
A 21
43.8%
S 12
25.0%
N 6
 
12.5%
Y 4
 
8.3%
K 2
 
4.2%
T 1
 
2.1%
E 1
 
2.1%
H 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 301
92.0%
Common 26
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 40
13.3%
r 23
 
7.6%
e 23
 
7.6%
i 22
 
7.3%
A 21
 
7.0%
y 19
 
6.3%
o 15
 
5.0%
s 14
 
4.7%
l 13
 
4.3%
u 12
 
4.0%
Other values (18) 99
32.9%
Common
ValueCountFrequency (%)
/ 22
84.6%
_ 4
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 40
 
12.2%
r 23
 
7.0%
e 23
 
7.0%
i 22
 
6.7%
/ 22
 
6.7%
A 21
 
6.4%
y 19
 
5.8%
o 15
 
4.6%
s 14
 
4.3%
l 13
 
4.0%
Other values (20) 115
35.2%

_embedded.show.network.officialSite
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)33.3%
Missing159
Missing (%)93.0%
Memory size1.5 KiB
https://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC
https://disneynow.com/all-shows/disney-channel
https://www.mavtv.com/
https://ici.radio-canada.ca/tele

Length

Max length64
Median length64
Mean length54.833333
Min length22

Characters and Unicode

Total characters658
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st rowhttps://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC
2nd rowhttps://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC
3rd rowhttps://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC
4th rowhttps://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC
5th rowhttps://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC

Common Values

ValueCountFrequency (%)
https://www.foxtel.com.au/tv-guide.html/channel/FOX-SHOWCASE/SHC 8
 
4.7%
https://disneynow.com/all-shows/disney-channel 2
 
1.2%
https://www.mavtv.com/ 1
 
0.6%
https://ici.radio-canada.ca/tele 1
 
0.6%
(Missing) 159
93.0%

Length

2023-08-13T15:45:17.556957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-13T15:45:17.613925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
https://www.foxtel.com.au/tv-guide.html/channel/fox-showcase/shc 8
66.7%
https://disneynow.com/all-shows/disney-channel 2
 
16.7%
https://www.mavtv.com 1
 
8.3%
https://ici.radio-canada.ca/tele 1
 
8.3%

Most occurring characters

ValueCountFrequency (%)
/ 62
 
9.4%
t 50
 
7.6%
. 38
 
5.8%
h 32
 
4.9%
e 32
 
4.9%
w 31
 
4.7%
l 31
 
4.7%
n 27
 
4.1%
a 26
 
4.0%
c 24
 
3.6%
Other values (24) 305
46.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 413
62.8%
Other Punctuation 112
 
17.0%
Uppercase Letter 112
 
17.0%
Dash Punctuation 21
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 50
12.1%
h 32
 
7.7%
e 32
 
7.7%
w 31
 
7.5%
l 31
 
7.5%
n 27
 
6.5%
a 26
 
6.3%
c 24
 
5.8%
o 24
 
5.8%
m 20
 
4.8%
Other values (11) 116
28.1%
Uppercase Letter
ValueCountFrequency (%)
S 24
21.4%
O 16
14.3%
H 16
14.3%
C 16
14.3%
F 8
 
7.1%
X 8
 
7.1%
W 8
 
7.1%
A 8
 
7.1%
E 8
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 62
55.4%
. 38
33.9%
: 12
 
10.7%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 525
79.8%
Common 133
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 50
 
9.5%
h 32
 
6.1%
e 32
 
6.1%
w 31
 
5.9%
l 31
 
5.9%
n 27
 
5.1%
a 26
 
5.0%
c 24
 
4.6%
S 24
 
4.6%
o 24
 
4.6%
Other values (20) 224
42.7%
Common
ValueCountFrequency (%)
/ 62
46.6%
. 38
28.6%
- 21
 
15.8%
: 12
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 62
 
9.4%
t 50
 
7.6%
. 38
 
5.8%
h 32
 
4.9%
e 32
 
4.9%
w 31
 
4.7%
l 31
 
4.7%
n 27
 
4.1%
a 26
 
4.0%
c 24
 
3.6%
Other values (24) 305
46.4%
Distinct7
Distinct (%)100.0%
Missing164
Missing (%)95.9%
Memory size1.5 KiB
2023-08-13T15:45:17.778475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters273
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2580326
2nd rowhttps://api.tvmaze.com/episodes/2550406
3rd rowhttps://api.tvmaze.com/episodes/2617844
4th rowhttps://api.tvmaze.com/episodes/2555884
5th rowhttps://api.tvmaze.com/episodes/2545839
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2580326 1
14.3%
https://api.tvmaze.com/episodes/2550406 1
14.3%
https://api.tvmaze.com/episodes/2617844 1
14.3%
https://api.tvmaze.com/episodes/2555884 1
14.3%
https://api.tvmaze.com/episodes/2545839 1
14.3%
https://api.tvmaze.com/episodes/2572533 1
14.3%
https://api.tvmaze.com/episodes/2493258 1
14.3%
2023-08-13T15:45:18.019793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 28
 
10.3%
p 21
 
7.7%
s 21
 
7.7%
e 21
 
7.7%
t 21
 
7.7%
o 14
 
5.1%
a 14
 
5.1%
i 14
 
5.1%
. 14
 
5.1%
m 14
 
5.1%
Other values (16) 91
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 175
64.1%
Other Punctuation 49
 
17.9%
Decimal Number 49
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 21
12.0%
s 21
12.0%
e 21
12.0%
t 21
12.0%
o 14
8.0%
a 14
8.0%
i 14
8.0%
m 14
8.0%
h 7
 
4.0%
d 7
 
4.0%
Other values (3) 21
12.0%
Decimal Number
ValueCountFrequency (%)
5 11
22.4%
2 10
20.4%
8 6
12.2%
4 6
12.2%
3 5
10.2%
0 3
 
6.1%
6 3
 
6.1%
7 2
 
4.1%
9 2
 
4.1%
1 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 28
57.1%
. 14
28.6%
: 7
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 175
64.1%
Common 98
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 28
28.6%
. 14
14.3%
5 11
 
11.2%
2 10
 
10.2%
: 7
 
7.1%
8 6
 
6.1%
4 6
 
6.1%
3 5
 
5.1%
0 3
 
3.1%
6 3
 
3.1%
Other values (3) 5
 
5.1%
Latin
ValueCountFrequency (%)
p 21
12.0%
s 21
12.0%
e 21
12.0%
t 21
12.0%
o 14
8.0%
a 14
8.0%
i 14
8.0%
m 14
8.0%
h 7
 
4.0%
d 7
 
4.0%
Other values (3) 21
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 28
 
10.3%
p 21
 
7.7%
s 21
 
7.7%
e 21
 
7.7%
t 21
 
7.7%
o 14
 
5.1%
a 14
 
5.1%
i 14
 
5.1%
. 14
 
5.1%
m 14
 
5.1%
Other values (16) 91
33.3%

Interactions

2023-08-13T15:45:02.142890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:52.557742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.411773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.137545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.900228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.579392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.268031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.074382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.754006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.451473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.161498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.940249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.632202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.367077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.190480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:52.670006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.462996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.187051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.948126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.629890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.318658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.120401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.802393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.504549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.211337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.989003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.683330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.417593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.243628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:52.770583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.517411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.238568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.000022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.680991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.375671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.172151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.854034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.554720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.339620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.043108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.740355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.471328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.292676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:52.836998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.566974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.284939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.047819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.726943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.425226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.221309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.903916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.608314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.386817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.090095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.791363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.519084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.342822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:52.889616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.617752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.335504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.093755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.773380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.475252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.267864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.950258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.657183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.433517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.138056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.842026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.567248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.389470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:52.947234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.669396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.450869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.142128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.823857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.529110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.311495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.006671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.706516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.487190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.188287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.895848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.617502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.440916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.003085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.726567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.501562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.194639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.874755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.591848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.361641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.057896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.758079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.538797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.242335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.950961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.669726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.488253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.057522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.777600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.551816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.240485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.918167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.641130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.410718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.105876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.807033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.587102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.289124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.001953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.716570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.538596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.110140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.825888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.603403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.286246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.971814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.688840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.456404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.150607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.863151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.642472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.336963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.052068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.764069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.589504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.162337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.878676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.656979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.336509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.019120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.742284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.508351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.206923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.914927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.693589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.389015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.106033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.889587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.636945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.212162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.928724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.704568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.383945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.073793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.792328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.553550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.253757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.962472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.741629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.437662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.157586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.938810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.681452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.260606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.980096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.752333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.430856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.122214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.916849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.604423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.301792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.011902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.789998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.485930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.208838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.987836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.734093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.313701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.034950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.804008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.483133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.174132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.973172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.655972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.354775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.063718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.843639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.539305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.264061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.041033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.788587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:53.361784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.085472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:54.851190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:55.529900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:56.222925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.024265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:57.704336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:58.402714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.111600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:44:59.891919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:00.587484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:01.315186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-13T15:45:02.088424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-13T15:45:18.187164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
idseasonnumberruntimerating.average_embedded.show.id_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.rating.average_embedded.show.weight_embedded.show.webChannel.id_embedded.show.externals.thetvdb_embedded.show.updated_embedded.show.network.idtypeairtimeairstamp_embedded.show.type_embedded.show.language_embedded.show.status_embedded.show.ended_embedded.show.schedule.time_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.externals.tvrage_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite
id1.0000.0470.114-0.370-0.0630.383-0.447-0.359-0.323-0.518-0.0800.144-0.0580.6020.0000.0000.2210.2500.2870.1770.3310.0000.3320.3320.3320.4981.0000.4230.4230.4230.894
season0.0471.0000.394-0.0000.161-0.7020.1710.012-0.2270.232-0.118-0.8100.3580.2110.0000.3090.2780.4050.0000.1561.0000.0000.0000.0000.0000.3001.0000.0000.0000.0001.000
number0.1140.3941.000-0.3210.142-0.387-0.378-0.325-0.052-0.033-0.267-0.4400.322-0.0631.0000.5120.5270.2680.0000.1770.8730.4840.3420.3420.3420.4481.0000.7390.7390.7390.894
runtime-0.370-0.000-0.3211.000-0.136-0.2170.9720.977-0.0630.173-0.0210.006-0.0070.2010.7000.0000.4090.4550.4770.0000.2200.3980.5610.5610.5610.767NaN0.6190.6190.6190.610
rating.average-0.0630.1610.142-0.1361.000-0.042NaN-0.0360.609-0.3950.301-0.1740.101NaN0.9310.3920.3910.7880.6870.3300.6400.5770.7380.7380.7380.677NaN1.0001.0001.0001.000
_embedded.show.id0.383-0.702-0.387-0.217-0.0421.000-0.365-0.1880.247-0.4980.1550.726-0.2930.1190.4080.4060.3750.2640.0770.1850.5990.3230.2550.2550.2550.4461.0000.7830.7830.7830.943
_embedded.show.runtime-0.4470.171-0.3780.972NaN-0.3651.0000.9900.2930.1820.199-0.3900.0740.4510.6760.0000.4000.4700.4740.0540.6330.3470.5650.5650.5650.7580.0000.5300.5300.5300.707
_embedded.show.averageRuntime-0.3590.012-0.3250.977-0.036-0.1880.9901.000-0.0030.203-0.0350.017-0.0440.2240.6910.0000.3470.4120.5760.1210.2110.3370.6060.6060.6060.6871.0000.5650.5650.5650.894
_embedded.show.rating.average-0.323-0.227-0.052-0.0630.6090.2470.293-0.0031.0000.1580.3610.1680.360-0.6380.0000.3760.4030.3580.0000.3770.5550.4580.3140.3140.3140.527NaN0.0000.0000.0001.000
_embedded.show.weight-0.5180.232-0.0330.173-0.395-0.4980.1820.2030.1581.000-0.132-0.3690.330-0.3300.0930.2640.3760.1970.4030.3460.5340.2370.4580.4580.4580.5331.0000.7140.7140.7141.000
_embedded.show.webChannel.id-0.080-0.118-0.267-0.0210.3010.1550.199-0.0350.361-0.1321.0000.1240.0570.3560.1080.3000.4700.1520.3820.3740.4830.3420.5390.5390.5390.8821.0000.8250.8250.8251.000
_embedded.show.externals.thetvdb0.144-0.810-0.4400.006-0.1740.726-0.3900.0170.168-0.3690.1241.000-0.262-0.3070.2860.5430.5690.3510.2050.1410.7530.4790.3280.3280.3280.5101.0000.7960.7960.7961.000
_embedded.show.updated-0.0580.3580.322-0.0070.101-0.2930.074-0.0440.3600.3300.057-0.2621.0000.1380.0200.2870.3750.1700.3360.4730.4250.2820.4130.4130.4130.6001.0000.6410.6410.6411.000
_embedded.show.network.id0.6020.211-0.0630.201NaN0.1190.4510.224-0.638-0.3300.356-0.3070.1381.0000.4470.6310.7470.7230.5880.7380.5770.8310.8380.8380.8380.8530.0000.6760.6760.6761.000
type0.0000.0001.0000.7000.9310.4080.6760.6910.0000.0930.1080.2860.0200.4471.0000.2460.1490.3820.3890.0001.0000.2450.0000.0000.0000.8551.0000.3870.3870.3871.000
airtime0.0000.3090.5120.0000.3920.4060.0000.0000.3760.2640.3000.5430.2870.6310.2461.0000.8710.2710.2110.4090.7860.8430.4130.4130.4130.7341.0000.6630.6630.6630.736
airstamp0.2210.2780.5270.4090.3910.3750.4000.3470.4030.3760.4700.5690.3750.7470.1490.8711.0000.3110.5090.4510.6700.8240.7840.7840.7840.8011.0000.7790.7790.7790.935
_embedded.show.type0.2500.4050.2680.4550.7880.2640.4700.4120.3580.1970.1520.3510.1700.7230.3820.2710.3111.0000.3290.3540.5130.2690.4130.4130.4130.4871.0000.6730.6730.6731.000
_embedded.show.language0.2870.0000.0000.4770.6870.0770.4740.5760.0000.4030.3820.2050.3360.5880.3890.2110.5090.3291.0000.4100.3950.3670.9590.9590.9590.6441.0000.9660.9660.9660.894
_embedded.show.status0.1770.1560.1770.0000.3300.1850.0540.1210.3770.3460.3740.1410.4730.7380.0000.4090.4510.3540.4101.0001.0000.1760.5510.5510.5510.6691.0000.2640.2640.2640.894
_embedded.show.ended0.3311.0000.8730.2200.6400.5990.6330.2110.5550.5340.4830.7530.4250.5771.0000.7860.6700.5130.3951.0001.0000.8560.6100.6100.6100.6980.0000.8160.8160.8161.000
_embedded.show.schedule.time0.0000.0000.4840.3980.5770.3230.3470.3370.4580.2370.3420.4790.2820.8310.2450.8430.8240.2690.3670.1760.8561.0000.4990.4990.4990.7521.0000.8020.8020.8021.000
_embedded.show.webChannel.country.name0.3320.0000.3420.5610.7380.2550.5650.6060.3140.4580.5390.3280.4130.8380.0000.4130.7840.4130.9590.5510.6100.4991.0001.0001.0000.889NaN0.9260.9260.9261.000
_embedded.show.webChannel.country.code0.3320.0000.3420.5610.7380.2550.5650.6060.3140.4580.5390.3280.4130.8380.0000.4130.7840.4130.9590.5510.6100.4991.0001.0001.0000.889NaN0.9260.9260.9261.000
_embedded.show.webChannel.country.timezone0.3320.0000.3420.5610.7380.2550.5650.6060.3140.4580.5390.3280.4130.8380.0000.4130.7840.4130.9590.5510.6100.4991.0001.0001.0000.889NaN0.9260.9260.9261.000
_embedded.show.webChannel.officialSite0.4980.3000.4480.7670.6770.4460.7580.6870.5270.5330.8820.5100.6000.8530.8550.7340.8010.4870.6440.6690.6980.7520.8890.8890.8891.0001.0000.9530.9530.9530.638
_embedded.show.externals.tvrage1.0001.0001.000NaNNaN1.0000.0001.000NaN1.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0000.0001.000NaNNaNNaN1.0001.0000.0000.0000.0000.000
_embedded.show.network.country.name0.4230.0000.7390.6191.0000.7830.5300.5650.0000.7140.8250.7960.6410.6760.3870.6630.7790.6730.9660.2640.8160.8020.9260.9260.9260.9530.0001.0001.0001.0000.943
_embedded.show.network.country.code0.4230.0000.7390.6191.0000.7830.5300.5650.0000.7140.8250.7960.6410.6760.3870.6630.7790.6730.9660.2640.8160.8020.9260.9260.9260.9530.0001.0001.0001.0000.943
_embedded.show.network.country.timezone0.4230.0000.7390.6191.0000.7830.5300.5650.0000.7140.8250.7960.6410.6760.3870.6630.7790.6730.9660.2640.8160.8020.9260.9260.9260.9530.0001.0001.0001.0000.943
_embedded.show.network.officialSite0.8941.0000.8940.6101.0000.9430.7070.8941.0001.0001.0001.0001.0001.0001.0000.7360.9351.0000.8940.8941.0001.0001.0001.0001.0000.6380.0000.9430.9430.9431.000

Missing values

2023-08-13T15:45:02.923236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-13T15:45:03.119506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-13T15:45:03.497079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.average_links.self.href_links.show.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href
02450906https://www.tvmaze.com/episodes/2450906/hocu-vse-znat-2x87-seria-87Серия 87287.0regular2022-12-012022-12-01T00:00:00+00:0012.0NoneNaNhttps://api.tvmaze.com/episodes/2450906https://api.tvmaze.com/shows/5572455724https://www.tvmaze.com/shows/55724/hocu-vse-znatХочу все знать!DocumentaryRussian[Children]Running12.012.02021-06-01Nonehttps://hd.kinopoisk.ru/film/4615b1810bb9c3bdb9c439fd701162a4[Thursday]NaN8381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/324/812265.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/812265.jpgNone1687434014https://api.tvmaze.com/shows/55724https://api.tvmaze.com/episodes/2575700NaNNaNNaNNaNNaNNaNNaNNaNNaN
12450907https://www.tvmaze.com/episodes/2450907/hocu-vse-znat-2x88-seria-88Серия 88288.0regular2022-12-012022-12-01T00:00:00+00:0012.0NoneNaNhttps://api.tvmaze.com/episodes/2450907https://api.tvmaze.com/shows/5572455724https://www.tvmaze.com/shows/55724/hocu-vse-znatХочу все знать!DocumentaryRussian[Children]Running12.012.02021-06-01Nonehttps://hd.kinopoisk.ru/film/4615b1810bb9c3bdb9c439fd701162a4[Thursday]NaN8381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/324/812265.jpghttps://static.tvmaze.com/uploads/images/original_untouched/324/812265.jpgNone1687434014https://api.tvmaze.com/shows/55724https://api.tvmaze.com/episodes/2575700NaNNaNNaNNaNNaNNaNNaNNaNNaN
22438114https://www.tvmaze.com/episodes/2438114/restoran-po-ponatiam-2x05-seria-15Серия 1525.0regular2022-12-012022-12-01T00:00:00+00:0030.0NoneNaNhttps://api.tvmaze.com/episodes/2438114https://api.tvmaze.com/shows/5920159201https://www.tvmaze.com/shows/59201/restoran-po-ponatiamРесторан по понятиямScriptedRussian[Comedy, Crime]To Be DeterminedNaN30.02022-01-20Nonehttps://premier.one/show/restoran-po-ponyatiyam[Tuesday, Thursday]NaN13281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/391/978564.jpghttps://static.tvmaze.com/uploads/images/original_untouched/391/978564.jpgNone1683640525https://api.tvmaze.com/shows/59201https://api.tvmaze.com/episodes/2438121NaNNaNNaNNaNNaNNaNNaNNaNNaN
32438115https://www.tvmaze.com/episodes/2438115/restoran-po-ponatiam-2x06-seria-16Серия 1626.0regular2022-12-012022-12-01T00:00:00+00:0030.0NoneNaNhttps://api.tvmaze.com/episodes/2438115https://api.tvmaze.com/shows/5920159201https://www.tvmaze.com/shows/59201/restoran-po-ponatiamРесторан по понятиямScriptedRussian[Comedy, Crime]To Be DeterminedNaN30.02022-01-20Nonehttps://premier.one/show/restoran-po-ponyatiyam[Tuesday, Thursday]NaN13281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/391/978564.jpghttps://static.tvmaze.com/uploads/images/original_untouched/391/978564.jpgNone1683640525https://api.tvmaze.com/shows/59201https://api.tvmaze.com/episodes/2438121NaNNaNNaNNaNNaNNaNNaNNaNNaN
42413779https://www.tvmaze.com/episodes/2413779/alisa-ne-mozet-zdat-1x08-8-seria8 серия18.0regular2022-12-0112:002022-12-01T00:00:00+00:0045.0NoneNaNhttps://api.tvmaze.com/episodes/2413779https://api.tvmaze.com/shows/6068760687https://www.tvmaze.com/shows/60687/alisa-ne-mozet-zdatАлиса не может ждатьScriptedRussian[]Ended50.044.02022-10-202022-12-01https://start.ru/watch/alisa-ne-mozhet-zhdat12:00[Monday]NaN8245.0StartRussian FederationRUAsia/KamchatkaNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/425/1064478.jpghttps://static.tvmaze.com/uploads/images/original_untouched/425/1064478.jpgNone1675623191https://api.tvmaze.com/shows/60687https://api.tvmaze.com/episodes/2413779NaNNaNNaNNaNNaNNaNNaNNaNNaN
52323161https://www.tvmaze.com/episodes/2323161/zamerzsie-1x01-seria-1Серия 111.0regular2022-12-012022-12-01T00:00:00+00:0050.0NoneNaNhttps://api.tvmaze.com/episodes/2323161https://api.tvmaze.com/shows/6188061880https://www.tvmaze.com/shows/61880/zamerzsieЗамерзшиеScriptedRussian[Drama, Thriller, Mystery]Ended50.0NaN2022-12-012022-12-01https://www.ivi.ru/watch/zamerzshie[]NaN19337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/407/1018744.jpghttps://static.tvmaze.com/uploads/images/original_untouched/407/1018744.jpgNone1676360040https://api.tvmaze.com/shows/61880https://api.tvmaze.com/episodes/2433632NaNNaNNaNNaNNaNNaNNaNNaNNaN
62433627https://www.tvmaze.com/episodes/2433627/zamerzsie-1x02-seria-2Серия 212.0regular2022-12-012022-12-01T00:00:00+00:0050.0NoneNaNhttps://api.tvmaze.com/episodes/2433627https://api.tvmaze.com/shows/6188061880https://www.tvmaze.com/shows/61880/zamerzsieЗамерзшиеScriptedRussian[Drama, Thriller, Mystery]Ended50.0NaN2022-12-012022-12-01https://www.ivi.ru/watch/zamerzshie[]NaN19337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/407/1018744.jpghttps://static.tvmaze.com/uploads/images/original_untouched/407/1018744.jpgNone1676360040https://api.tvmaze.com/shows/61880https://api.tvmaze.com/episodes/2433632NaNNaNNaNNaNNaNNaNNaNNaNNaN
72433628https://www.tvmaze.com/episodes/2433628/zamerzsie-1x03-seria-3Серия 313.0regular2022-12-012022-12-01T00:00:00+00:0050.0NoneNaNhttps://api.tvmaze.com/episodes/2433628https://api.tvmaze.com/shows/6188061880https://www.tvmaze.com/shows/61880/zamerzsieЗамерзшиеScriptedRussian[Drama, Thriller, Mystery]Ended50.0NaN2022-12-012022-12-01https://www.ivi.ru/watch/zamerzshie[]NaN19337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/407/1018744.jpghttps://static.tvmaze.com/uploads/images/original_untouched/407/1018744.jpgNone1676360040https://api.tvmaze.com/shows/61880https://api.tvmaze.com/episodes/2433632NaNNaNNaNNaNNaNNaNNaNNaNNaN
82433629https://www.tvmaze.com/episodes/2433629/zamerzsie-1x04-seria-4Серия 414.0regular2022-12-012022-12-01T00:00:00+00:0050.0NoneNaNhttps://api.tvmaze.com/episodes/2433629https://api.tvmaze.com/shows/6188061880https://www.tvmaze.com/shows/61880/zamerzsieЗамерзшиеScriptedRussian[Drama, Thriller, Mystery]Ended50.0NaN2022-12-012022-12-01https://www.ivi.ru/watch/zamerzshie[]NaN19337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/407/1018744.jpghttps://static.tvmaze.com/uploads/images/original_untouched/407/1018744.jpgNone1676360040https://api.tvmaze.com/shows/61880https://api.tvmaze.com/episodes/2433632NaNNaNNaNNaNNaNNaNNaNNaNNaN
92433630https://www.tvmaze.com/episodes/2433630/zamerzsie-1x05-seria-5Серия 515.0regular2022-12-012022-12-01T00:00:00+00:0050.0NoneNaNhttps://api.tvmaze.com/episodes/2433630https://api.tvmaze.com/shows/6188061880https://www.tvmaze.com/shows/61880/zamerzsieЗамерзшиеScriptedRussian[Drama, Thriller, Mystery]Ended50.0NaN2022-12-012022-12-01https://www.ivi.ru/watch/zamerzshie[]NaN19337.0iviRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/407/1018744.jpghttps://static.tvmaze.com/uploads/images/original_untouched/407/1018744.jpgNone1676360040https://api.tvmaze.com/shows/61880https://api.tvmaze.com/episodes/2433632NaNNaNNaNNaNNaNNaNNaNNaNNaN
idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.average_links.self.href_links.show.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href
1612466450https://www.tvmaze.com/episodes/2466450/la-rebelion-1x04-secreto-descubiertoSecreto descubierto14.0regular2022-12-012022-12-01T17:00:00+00:0039.0<p>They all discover Yvonne's secret and discuss what to do about it. Raymundo and Mauricio begin to approach the place where the 4 friends are hiding. Regina and Diego rush to find them first to warn them.</p>NaNhttps://api.tvmaze.com/episodes/2466450https://api.tvmaze.com/shows/6630966309https://www.tvmaze.com/shows/66309/la-rebelionLa RebeliónScriptedSpanish[Drama, Crime, Thriller]EndedNaN39.02022-11-172022-12-15https://vix.com/es/detail/series-3916[]NaN1552.0ViXUnited StatesUSAmerica/New_Yorkhttps://vix.com/NaN427796.0tt17048042https://static.tvmaze.com/uploads/images/medium_portrait/441/1102670.jpghttps://static.tvmaze.com/uploads/images/original_untouched/441/1102670.jpg<p>Four women decide to leave their homes unexpectedly without telling anyone their whereabouts, to rebel against their marriages and their lives as housewives that did not turn out as they thought. However, in addition to the trip, a murder will bring their lives together.</p>1673458918https://api.tvmaze.com/shows/66309https://api.tvmaze.com/episodes/2466452https://static.tvmaze.com/uploads/images/medium_landscape/441/1102948.jpghttps://static.tvmaze.com/uploads/images/original_untouched/441/1102948.jpgNaNNaNNaNNaNNaNNaNNaN
1622493865https://www.tvmaze.com/episodes/2493865/inside-monster-jam-1x14-krysten-and-weston-andersonKrysten and Weston Anderson114.0regular2022-12-012022-12-01T17:00:00+00:0042.0<p>Monster Jam athletes and siblings Krysten and Weston Anderson stop by on "Inside Monster Jam" to discuss life growing up in the Anderson household.</p>NaNhttps://api.tvmaze.com/episodes/2493865https://api.tvmaze.com/shows/6708267082https://www.tvmaze.com/shows/67082/inside-monster-jamInside Monster JamSportsEnglish[]Running30.032.02022-09-09Nonehttps://www.monsterjam.com/en-US/tv21:00[Saturday]NaN11NaNNaNNaNNaNNaNNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/452/1130129.jpghttps://static.tvmaze.com/uploads/images/original_untouched/452/1130129.jpg<p>This official Monster Jam podcast offers exclusive inside access to Monster Jam Operations, including drivers, safety, track design and the Monster Jam Garage.</p>1689175283https://api.tvmaze.com/shows/67082https://api.tvmaze.com/episodes/2493257NaNNaN739.0MAVTVUnited StatesUSAmerica/New_Yorkhttps://www.mavtv.com/https://api.tvmaze.com/episodes/2493258
1632459839https://www.tvmaze.com/episodes/2459839/bachelorette-sverige-3x12-avsnitt-12Avsnitt 12312.0regular2022-12-0119:002022-12-01T18:00:00+00:0060.0NoneNaNhttps://api.tvmaze.com/episodes/2459839https://api.tvmaze.com/shows/6220562205https://www.tvmaze.com/shows/62205/bachelorette-sverigeBachelorette SverigeRealitySwedish[Romance]Running60.060.02011-03-27Nonehttps://www.cmore.se/serie/221684-bachelorette-sverige19:00[Monday, Tuesday, Wednesday, Thursday]NaN2170.0C MoreSwedenSEEurope/StockholmNoneNaN248108.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/409/1024483.jpghttps://static.tvmaze.com/uploads/images/original_untouched/409/1024483.jpgA woman gets to know a group of single men to find her great love.1672613266https://api.tvmaze.com/shows/62205https://api.tvmaze.com/episodes/2459847NaNNaN558.0TV3SwedenSEEurope/StockholmNoneNaN
1642430343https://www.tvmaze.com/episodes/2430343/notruf-hafenkante-17x11-recht-und-unrechtRecht und Unrecht1711.0regular2022-12-0119:252022-12-01T18:25:00+00:0045.0NoneNaNhttps://api.tvmaze.com/episodes/2430343https://api.tvmaze.com/shows/1704617046https://www.tvmaze.com/shows/17046/notruf-hafenkanteNotruf HafenkanteScriptedGerman[Drama, Crime]Running45.050.02007-01-04Nonehttps://www.zdf.de/serien/notruf-hafenkante19:25[Thursday]NaN46352.0ZDFmediathekGermanyDEEurope/BusingenNoneNaN232731.0tt0940902https://static.tvmaze.com/uploads/images/medium_portrait/57/143179.jpghttps://static.tvmaze.com/uploads/images/original_untouched/57/143179.jpgNone1671264372https://api.tvmaze.com/shows/17046https://api.tvmaze.com/episodes/2450238NaNNaNNaNNaNNaNNaNNaNNaNNaN
1652419352https://www.tvmaze.com/episodes/2419352/husdrommar-sicilien-3x06-detta-ar-battre-an-mogel-i-varje-fallDetta är bättre än mögel i varje fall36.0regular2022-12-0121:002022-12-01T20:00:00+00:0030.0NoneNaNhttps://api.tvmaze.com/episodes/2419352https://api.tvmaze.com/shows/5821658216https://www.tvmaze.com/shows/58216/husdrommar-sicilienHusdrömmar: SicilienRealitySwedish[]Running30.030.02020-04-02Nonehttps://www.svtplay.se/husdrommar-sicilien21:00[Thursday]NaN19190.0SVT PlaySwedenSEEurope/Stockholmhttps://www.svtplay.se/NaN379487.0tt14432052https://static.tvmaze.com/uploads/images/medium_portrait/364/910029.jpghttps://static.tvmaze.com/uploads/images/original_untouched/364/910029.jpg<p>Join the former Husdrömmar couple Bill and Marie from Höganäs when they will realize their latest house dream in Sicily. The pink crow castle "Palazzo Cirillo" will be the family's new summer home. </p>1671227619https://api.tvmaze.com/shows/58216https://api.tvmaze.com/episodes/2419354https://static.tvmaze.com/uploads/images/medium_landscape/432/1081656.jpghttps://static.tvmaze.com/uploads/images/original_untouched/432/1081656.jpgNaNNaNNaNNaNNaNNaNNaN
1662501911https://www.tvmaze.com/episodes/2501911/infoman-23x11-episode-11Episode 112311.0regular2022-12-0119:302022-12-01T23:30:00+00:0030.0NoneNaNhttps://api.tvmaze.com/episodes/2501911https://api.tvmaze.com/shows/62206220https://www.tvmaze.com/shows/6220/infomanInfomanNewsFrench[Comedy]Running30.030.02012-02-09Nonehttp://infoman.radio-canada.ca/19:30[Thursday]NaN43301.0ICI Tou.tvCanadaCAAmerica/HalifaxNoneNaN83620.0tt0446222https://static.tvmaze.com/uploads/images/medium_portrait/407/1018747.jpghttps://static.tvmaze.com/uploads/images/original_untouched/407/1018747.jpg<p>The program whose original aim was simply to provide good, clean family entertainment has become an institution after 15 years on the air. Jean-René Dufort and his sidekicks, Chantal Lamarre and Mc Gilles, delight in the news events of the week.</p>1684361298https://api.tvmaze.com/shows/6220https://api.tvmaze.com/episodes/2550535NaNNaN451.0ICI Radio-Canada TéléCanadaCAAmerica/Halifaxhttps://ici.radio-canada.ca/teleNaN
1672434905https://www.tvmaze.com/episodes/2434905/puppy-dog-pals-5x33-wrap-party-pupsWrap Party Pups533.0regular2022-12-0119:002022-12-02T00:00:00+00:0015.0<p>The pets go on a mission to find Grace's gift before she needs to swap presents.</p>NaNhttps://api.tvmaze.com/episodes/2434905https://api.tvmaze.com/shows/2634126341https://www.tvmaze.com/shows/26341/puppy-dog-palsPuppy Dog PalsAnimationEnglish[Comedy, Children]Ended15.015.02017-04-142023-01-20https://disneynow.com/shows/puppy-dog-pals08:30[Friday]8.08783.0DisneyNOWUnited StatesUSAmerica/New_Yorkhttps://disneynow.com/NaN325978.0tt6688750https://static.tvmaze.com/uploads/images/medium_portrait/136/342487.jpghttps://static.tvmaze.com/uploads/images/original_untouched/136/342487.jpg<p><b>Puppy Dog Pals </b>is about fun-loving pug puppies, brothers Bingo and Rolly, have thrill-seeking appetites that take them on exhilarating adventures in their neighborhood and around the globe. Whether helping their owner Bob or assisting a friend in need, the pugs' motto is that life is more exciting with your best friend by your side. Each episode features two 11-minute stories that showcase Bingo and Rolly's similarities and differences while demonstrating positive lessons about friendship, problem-solving, collaboration, creativity and adventure.</p>1678525606https://api.tvmaze.com/shows/26341https://api.tvmaze.com/episodes/2452008NaNNaN78.0Disney ChannelUnited StatesUSAmerica/New_Yorkhttps://disneynow.com/all-shows/disney-channelNaN
1682436366https://www.tvmaze.com/episodes/2436366/de-ferias-com-o-ex-brasil-9x06-episodio-6Episódio 696.0regular2022-12-0122:002022-12-02T00:00:00+00:0060.0NoneNaNhttps://api.tvmaze.com/episodes/2436366https://api.tvmaze.com/shows/3914539145https://www.tvmaze.com/shows/39145/de-ferias-com-o-ex-brasilDe Férias com o Ex BrasilRealityPortuguese[Romance]Running60.060.02018-05-17Nonehttps://www.mtv.com.br/programas/aej2gj/de-ferias-com-o-ex-brasil22:00[Tuesday, Thursday]NaN61NaNNaNNaNNaNNaNNaNNaN348106.0tt8470764https://static.tvmaze.com/uploads/images/medium_portrait/410/1025124.jpghttps://static.tvmaze.com/uploads/images/original_untouched/410/1025124.jpgNone1684343502https://api.tvmaze.com/shows/39145https://api.tvmaze.com/episodes/2550436NaNNaN1366.0MTV BrasilBrazilBRAmerica/NoronhaNoneNaN
1692439198https://www.tvmaze.com/episodes/2439198/de-ferias-com-o-ex-brasil-s09-special-no-estudio-com-o-ex-caribe-s02e06No Estúdio com o Ex Caribe S02E069NaNinsignificant_special2022-12-0122:002022-12-02T00:00:00+00:0060.0NoneNaNhttps://api.tvmaze.com/episodes/2439198https://api.tvmaze.com/shows/3914539145https://www.tvmaze.com/shows/39145/de-ferias-com-o-ex-brasilDe Férias com o Ex BrasilRealityPortuguese[Romance]Running60.060.02018-05-17Nonehttps://www.mtv.com.br/programas/aej2gj/de-ferias-com-o-ex-brasil22:00[Tuesday, Thursday]NaN61NaNNaNNaNNaNNaNNaNNaN348106.0tt8470764https://static.tvmaze.com/uploads/images/medium_portrait/410/1025124.jpghttps://static.tvmaze.com/uploads/images/original_untouched/410/1025124.jpgNone1684343502https://api.tvmaze.com/shows/39145https://api.tvmaze.com/episodes/2550436NaNNaN1366.0MTV BrasilBrazilBRAmerica/NoronhaNoneNaN
1702434906https://www.tvmaze.com/episodes/2434906/puppy-dog-pals-5x34-fixing-santas-sleighFixing Santa's Sleigh534.0regular2022-12-0119:152022-12-02T00:15:00+00:0015.0<p>When Santa's sleigh breaks down mid-delivery, the pets make it their mission to fix it.</p>NaNhttps://api.tvmaze.com/episodes/2434906https://api.tvmaze.com/shows/2634126341https://www.tvmaze.com/shows/26341/puppy-dog-palsPuppy Dog PalsAnimationEnglish[Comedy, Children]Ended15.015.02017-04-142023-01-20https://disneynow.com/shows/puppy-dog-pals08:30[Friday]8.08783.0DisneyNOWUnited StatesUSAmerica/New_Yorkhttps://disneynow.com/NaN325978.0tt6688750https://static.tvmaze.com/uploads/images/medium_portrait/136/342487.jpghttps://static.tvmaze.com/uploads/images/original_untouched/136/342487.jpg<p><b>Puppy Dog Pals </b>is about fun-loving pug puppies, brothers Bingo and Rolly, have thrill-seeking appetites that take them on exhilarating adventures in their neighborhood and around the globe. Whether helping their owner Bob or assisting a friend in need, the pugs' motto is that life is more exciting with your best friend by your side. Each episode features two 11-minute stories that showcase Bingo and Rolly's similarities and differences while demonstrating positive lessons about friendship, problem-solving, collaboration, creativity and adventure.</p>1678525606https://api.tvmaze.com/shows/26341https://api.tvmaze.com/episodes/2452008NaNNaN78.0Disney ChannelUnited StatesUSAmerica/New_Yorkhttps://disneynow.com/all-shows/disney-channelNaN